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Journal articles on the topic 'Fuzzy addition operation'
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1
Zhu, Lin, Xiangfu Meng, and Zehui Mi. "Fuzzy Spatiotemporal Data Modeling and Operations in RDF." Information 13, no. 10 (2022): 503. http://dx.doi.org/10.3390/info13100503.
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With the emergence of a large number of fuzzy spatiotemporal data on the Web, how to represent and operate fuzzy spatiotemporal data has become an important research issue. Meanwhile, the Resource Description Framework (RDF) is a standard data and knowledge description language of the Semantic Web and has been applied in many application areas, such as geographic information systems and meteorological systems. In this paper, a model for representing fuzzy spatiotemporal data is proposed and a set of algebraic operations for the model are investigated. First, a representation method of fuzzy spatiotemporal RDF data and a fuzzy spatiotemporal RDF graph model are proposed. In addition, a formal fuzzy spatiotemporal RDF algebra is proposed and a set of algebraic operations for manipulating fuzzy spatiotemporal RDF data are developed. The algebraic operations include: set operation, selection operation, projection operation, join operation, and construction operation. Finally, the existing SPARQL query language is extended and an example that shows how to apply the proposed algebraic operations to capture the queries expressed by the extended SPARQL query language is given.
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Qin, Na, and Zengtai Gong. "Special Discrete Fuzzy Numbers on Countable Sets and Their Applications." Symmetry 16, no. 3 (2024): 264. http://dx.doi.org/10.3390/sym16030264.
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There are some drawbacks to arithmetic and logic operations of general discrete fuzzy numbers, which limit their application. For example, the result of the addition operation of general discrete fuzzy numbers defined by the Zadeh’s extension principle may not satisfy the condition of becoming a discrete fuzzy number. In order to solve these problems, special discrete fuzzy numbers on countable sets are investigated in this paper. Since the representation theorem of fuzzy numbers is the basic tool of fuzzy analysis, two kinds of representation theorems of special discrete fuzzy numbers on countable sets are studied first. Then, the metrics of special discrete fuzzy numbers on countable sets are defined, and the relationship between these metrics and the uniform Hausdorff metric (i.e., supremum metric) of general fuzzy numbers is discussed. In addition, the triangular norm and triangular conorm operations (t-norm and t-conorm for short) of special discrete fuzzy numbers on countable sets are presented, and the properties of these two operators are proven. We also prove that these two operators satisfy the basic conditions for closure of operation and present some examples. Finally, the applications of special discrete fuzzy numbers on countable sets in image fusion and aggregation of subjective evaluation are proposed.
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Piegat, Andrzej, and Marcin Pluciński. "Fuzzy Number Addition with the Application of Horizontal Membership Functions." Scientific World Journal 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/367214.
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The paper presents addition of fuzzy numbers realised with the application of the multidimensional RDM arithmetic and horizontal membership functions (MFs). Fuzzy arithmetic (FA) is a very difficult task because operations should be performed here on multidimensional information granules. Instead, a lot of FA methods useα-cuts in connection with 1-dimensional classical interval arithmetic that operates not on multidimensional granules but on 1-dimensional intervals. Such approach causes difficulties in calculations and is a reason for arithmetical paradoxes. The multidimensional approach allows for removing drawbacks and weaknesses of FA. It is possible thanks to the application of horizontal membership functions which considerably facilitate calculations because now uncertain values can be inserted directly into equations without using the extension principle. The paper shows how the addition operation can be realised on independent fuzzy numbers and on partly or fully dependent fuzzy numbers with taking into account the order relation and how to solve equations, which can be a difficult task for 1-dimensional FAs.
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Khalil, Ahmed Mostafa, Dunqian Cao, Abdelfatah Azzam, Florentin Smarandache, and Wedad R. Alharbi. "Combination of the Single-Valued Neutrosophic Fuzzy Set and the Soft Set with Applications in Decision-Making." Symmetry 12, no. 8 (2020): 1361. http://dx.doi.org/10.3390/sym12081361.
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In this article, we propose a novel concept of the single-valued neutrosophic fuzzy soft set by combining the single-valued neutrosophic fuzzy set and the soft set. For possible applications, five kinds of operations (e.g., subset, equal, union, intersection, and complement) on single-valued neutrosophic fuzzy soft sets are presented. Then, several theoretical operations of single-valued neutrosophic fuzzy soft sets are given. In addition, the first type for the fuzzy decision-making based on single-valued neutrosophic fuzzy soft set matrix is constructed. Finally, we present the second type by using the AND operation of the single-valued neutrosophic fuzzy soft set for fuzzy decision-making and clarify its applicability with a numerical example.
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Lu, Hanchuan, Ahmed Mostafa Khalil, W. Alharbi, and M. A. El-Gayar. "A new type of generalized picture fuzzy soft set and its application in decision making." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 12459–75. http://dx.doi.org/10.3233/jifs-201706.
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In this article, we propose a novel concept of the generalized picture fuzzy soft set by combining the picture fuzzy soft set and the fuzzy parameter set. For possible applications, we explain five kinds of operations (e.g., subset, equal, union, intersection, and complement) based on generalized picture fuzzy soft sets. Then, we establish several theoretical operations of generalized picture fuzzy soft sets. In addition, we present the new type by using the AND operation of the generalized picture fuzzy soft set for fuzzy decision-making and clarify its applicability with a numerical example. Finally, we give a comparison between the picture fuzzy soft set theory and the generalized picture fuzzy soft set theory. It is shown that our proposed (i.e., generalized picture fuzzy soft set theory) is viable and provide decision makers a more mathematical insight before making decisions on their options.
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Lev, Raskin, and Sira Oksana. "PERFORMING ARITHMETIC OPERATIONS OVER THE (L–R)-TYPE FUZZY NUMBERS." Eastern-European Journal of Enterprise Technologies 3, no. 4 (105) (2020): 6–11. https://doi.org/10.15587/1729-4061.2020.203590.
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The issue of constructing a system of rules to perform binary operations over fuzzy numbers has been formulated and considered. The set problem has been solved regarding the (<em>L</em>–<em>R</em>)-type fuzzy numbers with a compact carrier. Such a problem statement is predetermined by the simplicity of the analytical notation of these numbers, thereby making it possible to unambiguously set a fuzzy number by a set of values of its parameters. This makes it possible, as regards the (<em>L</em>–<em>R</em>)-type numbers, to reduce the desired execution rules for fuzzy numbers to the rules for simple arithmetic operations over their parameters. It has been established that many cited works provide ratios that describe the rules for performing operations over the (<em>L</em>–<em>R</em>)-type fuzzy numbers that contain errors. In addition, there is no justification for these rules in all cases. In order to build a correct system of fuzzy arithmetic rules, a set of metarules has been proposed, which determine the principles of construction and the structure of rules for operation execution. Using this set of metarules has enabled the development and description of the system of rules for performing basic arithmetic operations (addition, subtraction, multiplication, division). In this case, different rules are given for the multiplication and division rules, depending on the position of the number carriers involved in the operation, relative to zero. The proposed rule system makes it possible to correctly solve many practical problems whose raw data are not clearly defined. This system of rules for fuzzy numbers with a compact carrier has been expanded to the case involving a non-finite carrier. The relevant approach has been implemented by a two-step procedure. The advantages and drawbacks of this approach have been identified
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LEE, KEON-MYUNG, DONG-HOON KWANG, and HYUNG LEEK WANG. "A FUZZY NEURAL NETWORK MODEL FOR FUZZY INFERENCE AND RULE TUNING." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 02, no. 03 (1994): 265–77. http://dx.doi.org/10.1142/s0218488594000213.
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It is relatively easy to create rough fuzzy rules for a target system. However, it is time-consuming and difficult to fine-tune them for improving their behavior. Meanwhile, in the process of fuzzy inference the defuzzification operation takes most of the inferencing time. In this paper, we propose a fuzzy neural network model which makes it possible to tune fuzzy rules by employing neural networks and reduces the burden of defuzzification operation. In addition, to show the applicability of the proposed model we perform an experiment and present its result.
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Silambarasan, I., R. Udhayakumar, Florentin Smarandache, and Said Broumi. "Some Algebraic structures of Neutrosophic fuzzy sets." International Journal of Neutrosophic Science 19, no. 2 (2022): 30–41. http://dx.doi.org/10.54216/ijns.190203.
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The mathematical operations of convergence, association, supplement, arithmetical total, logarithmic item, scalar increase, and exponentiation are the main topics of this article. We show certain important logarithmic features of idempotency, commutativity, associativity, retention, distributivity, and De Morgan’s laws over the addition of Neutrosophic fuzzy sets. We also outline new fixations and NFS widening and show some concepts in action. Last but not least, we define a further operation (@)on Neutrosophic fuzzy sets and investigate distributive laws for the case where the responsibilities of ⊕, ⊗, ∪, and ∩ are combined.
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Ledeneva, Tatiana. "A Parametric Family of Triangular Norms and Conorms with an Additive Generator in the Form of an Arctangent of a Linear Fractional Function." Computation 11, no. 8 (2023): 155. http://dx.doi.org/10.3390/computation11080155.
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At present, fuzzy modeling has established itself as an effective tool for designing and developing systems for various purposes that are used to solve problems of control, diagnostics, forecasting, and decision making. One of the most important problems is the choice and justification of an appropriate functional representation of the main fuzzy operations. It is known that, in the class of rational functions, such operations can be represented by additive generators in the form of a linear fractional function, a logarithm of a linear fractional function, and an arctangent of a linear fractional function. The paper is devoted to the latter case. Restrictions on the parameters, under which the arctangent of a linear fractional function is an increasing or decreasing generator, are defined. For each case, a corresponding fuzzy operation (a triangular norm or a conorm) is constructed. The theoretical significance of the research results lies in the fact that the obtained parametric families enrich the theory of Archimedean triangular norms and conorms and provide additional opportunities for the functional representation of fuzzy operations in the framework of fuzzy modeling. In addition, in fact, we formed a scheme for study functions that can be considered additive generators and constructed the corresponding fuzzy operations.
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Piegat, A., and M. Pluciński. "Fuzzy number division and the multi-granularity phenomenon." Bulletin of the Polish Academy of Sciences Technical Sciences 65, no. 4 (2017): 497–511. http://dx.doi.org/10.1515/bpasts-2017-0055.
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AbstractThe paper presents difficulties connected with fuzzy and interval division. If operations such as fuzzy addition, subtraction and multiplication provide as a result one compact, multidimensional granule, then a result of the fuzzy division can consists of few separated granules. Such results are more difficult to use in next calculations. The paper shows that the number of solution granules can be higher than 2 and that in certain problems division does not occur explicitly. In certain problems, separation of particular solution granules can be considerable. The paper also shows how to realize the fuzzy division when its denominator contains zero. Most types of fuzzy arithmetics forbid such operation. However, the paper shows that it is possible. Multidimensional fuzzy RDM arithmetic and horizontal membership functions which facilitate detecting of solution granules are also described. The considered problems are visualized by examples.
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Markov, Svetoslav M., and Nathan T. Hayes. "On the Arithmetic of Errors." Serdica Journal of Computing 4, no. 4 (2011): 447–62. http://dx.doi.org/10.55630/sjc.2010.4.447-462.
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An approximate number is an ordered pair consisting of a (real) number and an error bound, briefly error, which is a (real) non-negative number. To compute with approximate numbers the arithmetic operations on errors should be well-known. To model computations with errors one should suitably define and study arithmetic operations and order relations over the set of non-negative numbers. In this work we discuss the algebraic properties of non-negative numbers starting from familiar properties of real numbers. We focus on certain operations of errors which seem not to have been sufficiently studied algebraically. In this work we restrict ourselves to arithmetic operations for errors related to addition and multiplication by scalars. We pay special attention to subtractability-like properties of errors and the induced “distance-like” operation. This operation is implicitly used under different names in several contemporary fields of applied mathematics (inner subtraction and inner addition in interval analysis, generalized Hukuhara difference in fuzzy set theory, etc.) Here we present some new results related to algebraic properties of this operation.
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Mohanad, Mohanad, Sinan O. Al Al-Salihi, and Faisal Al Al-Sharqi. "Development of a novel uncertainty model for interval-valued Q-fuzzy soft sets: Application in design-making." International Journal of Neutrosophic Science 24, no. 3 (2024): 65–76. http://dx.doi.org/10.54216/ijns.240306.
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In actual life, dealing with uncertain information has become a challenge for researchers who strive day after day to develop more accurate mathematical tools for better dealing with this information. The Q-Fuzzy soft model can process uncertain information in two dimensions by dealing with the subjective judgments of users effectively. Therefore, this article aims to increase the effectiveness of the Q-fuzzy soft model and address the challenges of design-making under uncertain information by proposing a new model called the interval-valued Q-fuzzy soft (IV-Q-FSS) model. Under the IV-Q-FSSs, we discuss strongly set-theory operations such as subset, union of two IV-Q-FSSs, intersection of two IV-Q-FSSs, complement of IV-Q-FSS, AND operation, and OR operation for IV-Q-FSSs, and some operations like the possibility and necessity operations of an IV-Q-FSS. In addition, we hand over numerous properties held up by numerical examples that describe how they toil. Finally, this recently developed model has been successfully trying out in dealing with one of the design-making problems based on hypothetical data for a respiratory disease. This algorithm is built based on the aggregation operator for IV-Q-FSS data to break this issue (i.e., selecting the optimal alternative).
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Pin, François G., and Yutaka Watanabe. "Navigation of mobile robots using a fuzzy behaviorist approach and custom-designed fuzzy inferencing boards." Robotica 12, no. 6 (1994): 491–503. http://dx.doi.org/10.1017/s0263574700016830.
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SummaryTwo types of computer boards incorporating recently developed VLSI fuzzy inferencing chips have been developed to support the addition of qualitative reasoning capabilities to the real-time control of robotic systems. The design and operation of these boards are first reviewed and their use, in conjunction with our proposed Fuzzy Behaviorist approach, is discussed. This approach uses superposition of elemental sensor-based behaviors expressed in the Fuzzy Sets theoretic framework, to emulate "human-like" reasoning inrobotic systems.
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Rudhito, Marcellinus Andy, Sri Wahyuni, Ari Suparwanto, and Frans Susilo. "Matriks atas Aljabar Max-Plus Interval." Jurnal Natur Indonesia 13, no. 2 (2012): 94. http://dx.doi.org/10.31258/jnat.13.2.94-99.
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This paper aims to discuss the matrix algebra over interval max-plus algebra (interval matrix) and a method tosimplify the computation of the operation of them. This matrix algebra is an extension of matrix algebra over max-plus algebra and can be used to discuss the matrix algebra over fuzzy number max-plus algebra via its alpha-cut.The finding shows that the set of all interval matrices together with the max-plus scalar multiplication operationand max-plus addition is a semimodule. The set of all square matrices over max-plus algebra together with aninterval of max-plus addition operation and max-plus multiplication operation is a semiring idempotent. As reasoningfor the interval matrix operations can be performed through the corresponding matrix interval, because thatsemimodule set of all interval matrices is isomorphic with semimodule the set of corresponding interval matrix,and the semiring set of all square interval matrices is isomorphic with semiring the set of the correspondingsquare interval matrix.
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Jafarova, Sh M. "SIMULATION OF FLEXIBLE PRODUCTION UNIT OPERATION USING PETRI NETS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 212 (February 2022): 19–25. http://dx.doi.org/10.14489/vkit.2022.02.pp.019-025.
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The article shows the sequence of developing a working model of active elements in the production of aluminum evaporators. Here, the development of a model for the operation of active elements in the production of aluminum evaporators is considered. The devices included in the flexible production model of the sewerage site are shown. The module shows the sequence of operations for air ducts on aluminum evaporators. Then, a fuzzy model of the activity of active elements of the flexible production supply chain model for the production of aluminum evaporators is described in the form of a fuzzy algebraic Petri net. The structure of flexible production systems has been developed. The network structure is obtained by determining the positions of the fuzzy algebraic Petri net, the number of links, as well as the input and output functions of each position and transition.After determining the structure of the fuzzy algebraic Petri net, a graph diagram of the operating model of the flexible production module of the site was built. In addition, an algorithm for automating and analyzing the operation of a fuzzy network of an algebraic Petri net has been developed. A description of the individual elements of the system and transitions is given, incidence matrices are given, an algorithm for automating and analyzing the activity of Petri nets, on the basis of which the sequence of transitions is analyzed, and individual transitions are described. Formulas for the analysis of restrictions are given. Based on the developed algorithm, a sequence of links developed in the original markup was obtained. The route of the robot was determined in the course of the developed markings. This route is presented in expanded link order. As a result, the cycle is repeated when loading and unloading the hydraulic press.
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Im, Hyunjun, Hyongdoo Jang, Erkan Topal, and Micah Nehring. "Long- and Short-Term Strategies for Estimation of Hydraulic Fracturing Cost Using Fuzzy Logic." Minerals 12, no. 6 (2022): 715. http://dx.doi.org/10.3390/min12060715.
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Over two decades, block caving mining has developed the application of hydraulic fracturing as a preconditioning method. This study aims to estimate hydraulic fracturing costs in block caving operations and suggests the base case of specified costs based on the U.S. Energy Information Administration (EIA) report. Furthermore, it applies cavability factors to develop the long- and short-term strategies through the fuzzy inference system. In the long-term strategy, we suggest three possible scenarios for reducing the long-term strategy’s uncertainty by considering the association for the advancement of cost engineering (AACE)’s contingency rate. Moreover, each fuzzy membership function of the three possible redeveloped scenarios was analysed through arithmetic operations over independent/dependent fuzzy numbers for comparing each scenario. The outcome of flexible cost estimation suggested deciding on the scale of infrastructure and ore production by facilitating undercut propagation and controlling block height of block caving operation including additional fragmentation processes. The result of this study also illustrated that systematic fuzzy cost engineering could help estimate the initial stage of budgeting. In addition, through solving the uncertainty of fuzzy calculation values, the project schedule identification is presented by recognising the dependence on each scenario’s common characteristic of the cavability parameter and cost contingency rate.
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Mojaveri, Hamidreza Salmani, and Vahid Moghimi. "Determination of Economic Order Quantity in a fuzzy EOQ Model using of GMIR Deffuzification." Indonesian Journal of Science and Technology 2, no. 1 (2017): 76. http://dx.doi.org/10.17509/ijost.v2i1.5990.
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Inappropriate inventory control policies and its incorrect implementation can cause improper operation and uncompetitive advantage of organization logistic operation in the market. Therefore, analysis inventory control policies are important to be understood, including carrying cost, ordering cost, warehouse renting cost, and buying cost. In this research, Economic Order Quantity (EOQ) problem in fuzzy condition is reviewed in two different situations. The first model concerned to costs (carrying cost, ordering cost, warehouse renting cost and buying cost), which is considered as triangular fuzzy numbers. The second model was in addition to inventory the cost system, in which annual demand is also reviewed as fuzzy numbers. In each model, graded mean integration representation (GMIR) deffuzification was used for parameters deffuzification. Then, the final objective from this analysis was to obtain economic quantity formula through derivation.
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Jafarpour, Amir, and Mehdi Najafi. "Selection of Compatible Coal Seam for Methane Drainage Operation Based on Uncertain Geological Conditions: A Hybrid Fuzzy Approach." Mathematical Problems in Engineering 2022 (April 12, 2022): 1–17. http://dx.doi.org/10.1155/2022/4586979.
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Geological studies are very important at different steps of mining activities. Different uncertain geological criteria and factors show a significant impact during the underground mining operations and mineral extraction process. The current study reports on the evaluation and classification of coal seams for methane drainage-ability (MDA) through a fuzzy hybrid approach. This problem was investigated due to the importance of uncertain geological factors in the process of MDA and the necessity to evaluate safety operations in underground coal mines. The important criteria involved are depth, thickness, and uniformity of coal seam, joints and cleats conditions, roof quality, coal seam gas content, underground water condition, and permeability of coal seam. The two-stage fuzzy classification approach was used to analyze the effectiveness of the uncertain geological criteria. Also, fuzzy cognitive map (FCM) method was used to calculate weights for geological criteria. The used FCM method is based on the Hebbian algorithm and metaheuristic methods. The Hebbian learning algorithm is made from a hybrid learning algorithm of nonlinear heuristics and differential evolution. In addition, fuzzy intervals of criteria were calculated based on technical reports and other scientific studies. Then, the rank of each coal seam calculates by fuzzy T-norms. The proposed system was employed to classify the coal seams for MDA in Parvadeh coalfield, Iran. The results showed that the C1, C2, B2, B1, and D coal seams were classified in the “very good,” “good,” “moderate,” “poor,” and “very poor” categories, respectively. The proposed fuzzy hybrid approach provides a new logical tool in the selection of coal seam for methane drainage operation and can reduce the risk of methane drainage projects in underground coal mines.
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Liu, Hongping, Ruiju Wei, and Qian Ge. "Convex structures in a new kind of ordered fuzzy group1." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 4245–57. http://dx.doi.org/10.3233/jifs-200311.
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By means of a fuzzy binary operation defined on partially ordered sets, a new kind of ordered fuzzy group is proposed in this paper. Some properties of this ordered fuzzy group are studied. Following that, its substructures, such as subgroup and convex subgroup, as well as its homomorphisms, along with their properties are explored. It is shown that each family of these substructures forms a convex structure, where the convex hull of a subset is exactly the (convex) subgroup generated by itself, and the homomorphisms between two ordered fuzzy groups are convexity-preserving mappings between the corresponding convex spaces. In addition, when these substructures are extended to fuzzy setting, several L-convex structures are constructed and investigated.
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Abdurrahman, Saman. "CROSS PRODUCT OF IDEAL FUZZY SEMIRING." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 2 (2023): 1131–38. http://dx.doi.org/10.30598/barekengvol17iss2pp1131-1138.
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If one of the axioms in the ring, namely the inverse axiom in the addition operation, is omitted, it will produce another algebraic structure, namely a semiring. Analogous to a ring, there are zero elements, ideal (left/right) in a semiring, and the cross product of the semiring ideal. The analog of the fuzzy semiring has zero elements, ideal (left/right), and the cross product of the semiring fuzzy ideal associated with the membership value. This paper will discuss the cross-product of two (more) fuzzy ideals from a semiring. Furthermore, the cross-product of two (more) fuzzy ideals from a semiring will always be a semiring fuzzy ideal. But the converse is not necessarily true.
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Mashadi, Yuliana Safitri, Sukono, Igif Gimin Prihanto, Muhamad Deni Johansyah, and Moch Panji Agung Saputra. "The Inverse and General Inverse of Trapezoidal Fuzzy Numbers with Modified Elementary Row Operations." Mathematics 12, no. 7 (2024): 946. http://dx.doi.org/10.3390/math12070946.
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Trapezoidal positive/negative fuzzy numbers have no single definition; instead, various authors define them in relation to different concepts. This means that arithmetic operations for trapezoidal fuzzy numbers also differ. For the operations of addition, subtraction, and scalar multiplication, there are not many differences; for multiplication, however, there are many differences. In general, multiplication is divided into various cases. For the inverse operation, there is not much to define; in general, for any trapezoidal fuzzy number u~, u~⊗1u~=i~=(1,1,0,0) does not necessarily apply. As a result of the different arithmetic operations for multiplication and division employed by various authors, several researchers have tackled the same problem and reached different solutions, meaning that the application will also produce different results. To date, many authors have proposed various alternatives for the algebra of the trapezoidal fuzzy number. In this paper, using the parametric form approach to trapezoidal fuzzy numbers, an alternative to multiplication with only one formula is constructed for various cases. Furthermore, based on the definition of multiplication for any trapezoidal fuzzy number, u~ is constructed 1u~ so that u~⊗1u~=i~=(1,1,0,0). Based on these conditions, we show that various properties that apply to real numbers also apply to any trapezoidal fuzzy number. Furthermore, we modify the elementary row operational steps for the trapezoidal fuzzy number matrix, which can be used to determine the inverse of a trapezoidal fuzzy number matrix with the order m×m. We also give the steps and examples necessary to determine the general inverse for a trapezoidal fuzzy number matrix of the order m×n with m ≠n. This ability to easily determine the inverse and general inverse of a trapezoidal fuzzy number matrix has a number of applications, such as solving fully trapezoidal fuzzy number linear systems and fuzzy transportation problems, especially in applications in fields outside of mathematics; for example, the application of triangular fuzzy numbers in medical problems is a topic currently receiving a significant amount of attention.
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Abdallah, Mohamed, Leta Fernandes, Mostafa Warith, and Septa Rendra. "A fuzzy logic model for biogas generation in bioreactor landfillsA paper submitted to the Journal of Environmental Engineering and Science." Canadian Journal of Civil Engineering 36, no. 4 (2009): 701–8. http://dx.doi.org/10.1139/l09-015.
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A fuzzy logic model was developed to simulate the effect of leachate recirculation and sludge addition on the biogas generation in anaerobic bioreactor landfills. The model was designed using a fuzzy logic system (FLS) which incorporated 3 input variables (time, leachate recirculation, and sludge addition) and a single manipulated output (biogas generation rate). The biogas production rate was measured during the experiment and was increasing proportionally with the rate of both leachate recirculation and sludge addition. The experimental work involved the operation of six simulated laboratory-scale bioreactors for over a year under different operating schemes. The experimental results were employed in formulating the fuzzy rule base, calibrating the model, and verifying its predictions. Then, the model was validated against other measured data that was compiled from published studies. The FLS model simulations demonstrated high correlation with the experimental observations.
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Zamyatin, Nikolaj, Gennadij Smirnov, Yuri Fedorchuk, and Olga Rusina. "Fuzzy batch controller for granular materials." MATEC Web of Conferences 143 (2018): 04003. http://dx.doi.org/10.1051/matecconf/201814304003.
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The paper focuses on batch control of granular materials in production of building materials from fluorine anhydrite. Batching equipment is intended for smooth operation and timely feeding of supply hoppers at a required level. Level sensors and a controller of an asynchronous screw drive motor are used to control filling of the hopper with industrial anhydrite binders. The controller generates a required frequency and ensures required productivity of a feed conveyor. Mamdani-type fuzzy inference is proposed for controlling the speed of the screw that feeds mixture components. As related to production of building materials based on fluoride anhydrite, this method is used for the first time. A fuzzy controller is proven to be effective in controlling the filling level of the supply hopper. In addition, the authors determined optimal parameters of the batching process to ensure smooth operation and production of fluorine anhydrite materials of specified properties that can compete with gypsum-based products.
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Abbasi, Fazlollah, Tofigh Allahviranloo, and Muhammad Akram. "A New Framework for Numerical Techniques for Fuzzy Nonlinear Equations." Axioms 12, no. 2 (2023): 222. http://dx.doi.org/10.3390/axioms12020222.
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This paper describes a computational method for solving the nonlinear equations with fuzzy input parameters that we encounter in engineering system analysis. In addition to discussing the existence of solutions, the definition and formalization of numerical solutions is based on a new fuzzy computation operation as a transmission average. Error analysis in numerical solutions is described. Finally, some examples are presented to implement the proposed method and its effectiveness compared to other previous methods.
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Abusorrah, Abdullah M. "Optimal Power Flow Using Adaptive Fuzzy Logic Controllers." Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/975170.
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This paper presents an approach for optimum reactive power dispatch through the power network with flexible AC transmission systems (FACTSs) devices, using adaptive fuzzy logic controller (AFLC) driven by adaptive fuzzy sets (AFSs). The membership functions of AFLC are optimized based on 2nd-order fuzzy set specifications. The operation of FACTS devices (particularly, static VAR compensator (SVC)) and the setting of their control parameters (QSVC) are optimized dynamically based on the proposed AFLC to enhance the power system stability in addition to their main function of power flow control. The proposed AFLC is compared with a static fuzzy logic controller (SFLC), driven by a fixed fuzzy set (FFS). Simulation studies were carried out and validated on the standard IEEE 30-bus test system.
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Javed, Mubashar, Shumaila Javeed, Jihad Ahmad, Kifayat Ullah, and Lemnaouar Zedam. "Approach to Multiattribute Decision-Making Problems Based on Neutrality Aggregation Operators of Picture Fuzzy Information." Journal of Function Spaces 2022 (April 1, 2022): 1–16. http://dx.doi.org/10.1155/2022/2762067.
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This manuscript is aimed at developing some novel operational laws named scalar neutrality operation and neutrality addition on picture fuzzy numbers (PFNs). The main focus of this work is to involve the neutral behaviour of the experts towards the priorities of entities where it presents equal degrees to independent membership functions. Moreover, based on these operations, some novel aggregation operators are established to aggregate the different priorities of experts. Some useful relations and characteristics are examined thoroughly. Lastly, the multiattribute group decision-making algorithm in accordance with the suggested operation is illustrated and examined a case study in order to choose a suitable mining company for a mining project along with several numerical examples. The advantages, as well as the superiority of the suggested approach, are exhibited by comparing the results with a few existing methods.
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Chen, Dingjun, Shaoquan Ni, Chang’an Xu, Hongxia Lv, and Keyun Qin. "A Soft Rough-Fuzzy Preference Set-Based Evaluation Method for High-Speed Train Operation Diagrams." Mathematical Problems in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/5795604.
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This paper proposes a method of high-speed railway train operation diagram evaluation based on preferences of locomotive operation, track maintenance, S & C, vehicles and other railway departments, and customer preferences. The application of rough set-based attribute reduction obtains the important relative indicators by eliminating excessive and redundant evaluation indicators. Soft fuzzy set theory is introduced for the overall evaluation of train operation diagrams. Each expert utilizes a set of indicators during evaluation based on personal preference. In addition, soft fuzzy set theory is applied to integrate the information obtained via expert evaluation in order to obtain an overall evaluation. The proposed method was validated by a case study. Results demonstrate that the proposed method flexibly expresses the subjective judgments of experts while effectively and reasonably handling the uncertainty of information, which is consistent with the judgment process of humans. The proposed method is also applicable to the evaluation of train operation schemes which consist of multiple diagrams.
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Zhang, Huimin. "Linguistic Intuitionistic Fuzzy Sets and Application in MAGDM." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/432092.
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To better deal with imprecise and uncertain information in decision making, the definition of linguistic intuitionistic fuzzy sets (LIFSs) is introduced, which is characterized by a linguistic membership degree and a linguistic nonmembership degree, respectively. To compare any two linguistic intuitionistic fuzzy values (LIFVs), the score function and accuracy function are defined. Then, based ont-norm andt-conorm, several aggregation operators are proposed to aggregate linguistic intuitionistic fuzzy information, which avoid the limitations in exiting linguistic operation. In addition, the desired properties of these linguistic intuitionistic fuzzy aggregation operators are discussed. Finally, a numerical example is provided to illustrate the efficiency of the proposed method in multiple attribute group decision making (MAGDM).
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Diao, Zhifeng, and Fanglei Sun. "Fuzzy Harmony Search Technique for Cyber Risks in Industry 4.0 Wireless Communication Networks." Processes 11, no. 3 (2023): 951. http://dx.doi.org/10.3390/pr11030951.
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Industry 4.0 houses diverse technologies including wireless communication and shared networks for internal and external operations. Due to the wireless nature and remote operability, the exposure to security threats is high. Cyber risk detection and mitigation are prominent for secure industrial operations and planned outcomes. In addition, the system faces the threat of intelligence attacks, security standards issues, privacy concerns and scalability problems. The cyber risk related research problems influence overall data transmission in industry wireless communication networks. For augmenting communication security through cyber risk detection, this article introduces an Explicit Risk Detection and Assessment Technique (ERDAT) for cyber threat mitigation in the industrial process. A fuzzy harmony search algorithm powers this technique for identifying the risk and preventing its impact. The harmony search algorithm mimics the adversary impact using production factors such as process interruption or halting and production outcome. The search performs a mimicking operation for a high objective function based on production output for the admitted plan. The fuzzy operation admits the above factors for identifying the cyber impacting risk, either for its impacts or profitable outcome. In this process, the fuzzy optimization identifies the maximum or minimum objective output targeted for either outcome or risk interrupts, respectively. The fuzzy threshold is identified using a mediated acceptable range, computed as the ratio between minimum and maximum, mimicking occurrences between the risk and scheduled production outcomes. Therefore, the mimicking crossing or falling behind the threshold for the interruption/halting or production, respectively, are identified as risks and their source is detected. The detection communication source is disconnected from the industrial process for preventing further adversary impacts. The introduced system achieves 8.52% high-risk detection, 12.5% fewer outcome interrupts, 8.3% fewer halted schedules, 8.08% less interrupt span, and 7.94% less detection time compared to traditional methods.
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Qiyas, Muhammad, Saleem Abdullah, Muhammad Naeem, Neelam Khan, Samuel Okyere, and Thongchi Botmart. "Decision Support System Based on Complex q -Rung Orthopair Fuzzy Rough Hamacher Aggregation Operator through Modified EDAS Method." Journal of Function Spaces 2022 (December 19, 2022): 1–18. http://dx.doi.org/10.1155/2022/5437373.
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The best mathematical tools for combining numerous inputs into a single result are aggregation operators. The aggregation operators work to combine all of the individual evaluation values provided in a uniform form, and they are very useful for evaluating the options provided in the decision-making process. To provide a larger space for decision makers, complex q -rung orthopair fuzzy rough sets can express their uncertain information. As a generalization of the algebraic operations, the Einstein t -norm and t -conorm, Hamacher operations have become significant in aggregation theory. The Hamacher aggregation operator’s major characteristic is that it can capture the interrelationship between several input arguments. In this article, some Hamacher aggregation operators for complex q -rung orthopair fuzzy rough sets are presented. We define a complex q -rung orthopair fuzzy rough Hamacher operation laws and a new score function. In addition, we propose a serious of averaging aggregation operators for complex q -rung orthopair fuzzy rough set. We present the essential properties of these operators. We use the defined operators and modified EDAS (evaluation based on distance from average solution) method to propose an approach for solving a multicriteria decision making problem. To demonstrate the practicality and effectiveness of our propose model, we consider a numerical example of area selection for an arboretum. Finally, a comparison between the suggested approach with existing operators has been presented for authenticity and reliability.
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Nozdrenkov, V. S., I. M. Diahovchenko, M. V. Petrovskyi, and V. V. Volokhin. "Fuzzy model of compensation for aging factors of distribution transformers." Electrical Engineering and Power Engineering, no. 2 (June 27, 2024): 7–17. http://dx.doi.org/10.15588/1607-6761-2024-2-1.
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Purpose. This paper aims to evaluate the negative factors that affect the aging of power distribution transformers, develop a fuzzy control model for their compensation, and study the results of applying the proposed model to different modes of the electrical power network. Methodology. The mathematical method of fuzzy logic was used to implement the control system of the power grid operating modes. Findings. The article presents a structure based on fuzzy logic for compensating depreciation factors of distribution transformers. A tuning algorithm and measures were developed to optimize the transformer's load level and power factor. The developed model analyzes the parameters and factors affecting the normal operation of the transformer and warns of dangerous factors that threaten reliability and may lead to a malfunction. In addition, the efficiency of PV generating stations, shunt capacitor banks, and energy storage systems installed on the secondary voltage side to preserve the service life of distribution transformers was analyzed and discussed. Originality. The paper further develops the fuzzy logic models used to optimize the operation of the power grid and compensate for the aging factors of power distribution transformers Practical value. The results obtained in the paper can be used to build an optimal system for controlling the operation modes of the electric power grid, which reduces the factors that accelerate the aging of power distribution transformers.
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Jacquin, Alexandra P., and Asaad Y. Shamseldin. "Review of the application of fuzzy inference systems in river flow forecasting." Journal of Hydroinformatics 11, no. 3-4 (2009): 202–10. http://dx.doi.org/10.2166/hydro.2009.038.
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This paper provides a general overview about the use of fuzzy inference systems in the important field of river flow forecasting. It discusses the overall operation of the main two types of fuzzy inference systems, namely Mamdani and Takagi–Sugeno–Kang fuzzy inference systems, and the critical issues related to their application. A literature review of existing studies dealing with the use of fuzzy inference systems in river flow forecasting models is presented, followed by some recommendations for future research areas. This review shows that fuzzy inference systems can be used as effective tools for river flow forecasting, even though their application is rather limited in comparison to the popularity of neural networks models. In addition to this, it was found that there are several unresolved issues requiring further attention before more clear guidelines for the application of fuzzy inference systems can be given.
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Cordova, Felisa M., and Guillermo Leyton. "A Fuzzy Control Heuristic Applied to Non-linear Dynamic System Using a Fuzzy Knowledge Representation." International Journal of Computers Communications & Control 5, no. 5 (2010): 664. http://dx.doi.org/10.15837/ijccc.2010.5.2222.
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This paper presents the design of a fuzzy control heuristic that can be applied for modeling nonlinear dynamic systems using a fuzzy knowledge representation. Nonlinear dynamic systems have been modeled traditionally on the basis of connections between the subsystems that compose it. Nevertheless, this model design does not consider some of the following problems: existing dynamics between the subsystems; order and priority of the connection between subsystems; degrees of influence or causality between subsystems; particular state of each subsystem and state of the system on the basis of the combination of the diverse states of the subsystems; positive or negative influences between subsystems. In this context, the main objective of this proposal is to manage the whole system state by managing the state combination of the subsystems involved. In the proposed design the diverse states of subsystems at different levels are represented by a knowledge base matrix of fuzzy intervals (KBMFI). This type of structure is a fuzzy hypercube that provides facilities operations like: insert, delete, and switching. It also allows Boolean operations between different KBMFI and inferences. Each subsystem in a specific level and its connectors are characterized by factors with fuzzy attributes represented by membership functions. Existing measures the degree of influence among the different levels are obtained (negatives, positives). In addition, the system state is determined based on the combination of the statements of the subsystems (stable, oscillatory, attractor, chaos). It allows introducing the dynamic effects in the calculation of each output level. The control and search of knowledge patterns are made by means of a fuzzy control heuristic. Finally, an application to the co-ordination of the activities among different levels of the operation of an underground mine is developed and discussed.
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Mokhtar, Touam, Chenafa Mohammed, Chekroun Soufyane, and Salim Ramzi. "Sensorless nonlinear sliding mode control of the induction machine at very low speed using FM-MRAS observer." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (2021): 1987–98. https://doi.org/10.11591/ijpeds.v12.i4.pp1987-1998.
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The induction motor is complex because its dynamic is nonlinear, multivariable and highly coupled. In addition, the induction motor (IM) controller design can be degraded due to wide ranges operating speed specially in low and near-zero speeds and also to variation of interval parameters such as the stator resistance change because of stator heating during operation. Our contribution is the use of a nonlinear sliding mode control using a fuzzy mutual reference adaptive system observer based on two fuzzy adaptation mechanisms to estimate both rotor speed and stator resistance. The proposed work was verified and compared by simulation and tested in various ranges of speed with motor and regenerating regions of operation. The results show that the proposed approach has proved good effectiveness in tracking and observation.
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Sheu, Ming-Hwa, S. M. Salahuddin Morsalin, Jia-Xiang Zheng, Shih-Chang Hsia, Cheng-Jian Lin, and Chuan-Yu Chang. "FGSC: Fuzzy Guided Scale Choice SSD Model for Edge AI Design on Real-Time Vehicle Detection and Class Counting." Sensors 21, no. 21 (2021): 7399. http://dx.doi.org/10.3390/s21217399.
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The aim of this paper is to distinguish the vehicle detection and count the class number in each classification from the inputs. We proposed the use of Fuzzy Guided Scale Choice (FGSC)-based SSD deep neural network architecture for vehicle detection and class counting with parameter optimization. The ‘FGSC’ blocks are integrated into the convolutional layers of the model, which emphasize essential features while ignoring less important ones that are not significant for the operation. We created the passing detection lines and class counting windows and connected them with the proposed FGSC-SSD deep neural network model. The ‘FGSC’ blocks in the convolution layer emphasize essential features and find out unnecessary features by using the scale choice method at the training stage and eliminate that significant speedup of the model. In addition, FGSC blocks avoided many unusable parameters in the saturation interval and improved the performance efficiency. In addition, the Fuzzy Sigmoid Function (FSF) increases the activation interval through fuzzy logic. While performing operations, the FGSC-SSD model reduces the computational complexity of convolutional layers and their parameters. As a result, the model tested Frames Per Second (FPS) on edge artificial intelligence (AI) and reached a real-time processing speed of 38.4 and an accuracy rate of more than 94%. Therefore, this work might be considered an improvement to the traffic monitoring approach by using edge AI applications.
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Touam, Mokhtar, Mohammed Chenafa, Soufyane Chekroun, and Ramzi Salim. "Sensorless nonlinear sliding mode control of the induction machine at very low speed using FM-MRAS observer." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (2021): 1987. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp1987-1998.
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<span lang="EN-US">The induction motor is complex because its dynamic is nonlinear, multivariable and highly coupled. In addition, the induction motor (IM) controller design can be degraded due to wide ranges operating speed specially in low and near-zero speeds and also to variation of interval parameters such as the stator resistance change because of stator heating during operation. Our contribution is the use of a nonlinear sliding mode control using a fuzzy mutual reference adaptive system observer based on two fuzzy adaptation mechanisms to estimate both rotor speed and stator resistance. The proposed work was verified and compared by simulation and tested in various ranges of speed with motor and regenerating regions of operation. The results show that the proposed approach has proved good effectiveness in tracking and observation.</span>
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Balin, Abit, Bekir Şener, and Hakan Demirel. "Application of fuzzy VIKOR method for the evaluation and selection of a suitable tugboat." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 234, no. 2 (2019): 502–9. http://dx.doi.org/10.1177/1475090219875879.
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Tugboats have a very critical role in numerous fields of the maritime sector. There are many types of tugboats with different characteristics that give superior results in different operations. Choosing the most suitable tugboat type for the desired operation is a multi-criteria problem that requires expertise. The design features of the tugboat and the propulsion system are important features used for classification. In addition, operational, environmental, and financial factors are also of considerable importance. In this article, determined criteria for tugboats classified according to their propulsion systems have been evaluated by subject-matter experts through a questionnaire. Fuzzy Shannon Entropy has been used to calculate the weights of each determined criterion. Then, fuzzy VIKOR was selected to rank the alternatives due to good compatibility with Entropy and the ability to adequately distinguish the table values that compose the ranking. Finally, the most suitable tugboat type was chosen in accordance with these results.
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Corona-Suárez, Gilberto A., Simaan M. AbouRizk, and Stanislav Karapetrovic. "Simulation-Based Fuzzy Logic Approach to Assessing the Effect of Project Quality Management on Construction Performance." Journal of Quality and Reliability Engineering 2014 (May 7, 2014): 1–18. http://dx.doi.org/10.1155/2014/203427.
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This paper reports the development of an approach to integrate the appropriate modeling techniques for estimating the effect of project quality management (PQM) on construction performance. This modeling approach features a causal structure that depicts the interaction among the PQM factors affecting quality performance in a given construction operation. In addition, it makes use of fuzzy sets and fuzzy logic in order to incorporate the subjectivity and uncertainty implicit in the performance assessment of these PQM factors to discrete-event simulation models. The outcome is a simulation approach that allows experimenting with different performance levels of the PQM practices implemented in a construction project and obtaining the corresponding productivity estimates of the construction operations. These estimates are intended to facilitate the decision making regarding the improvement of a PQM system implemented in a construction project. A case study is used to demonstrate the usefulness of the proposed simulation approach for evaluating diverse performance improvement alternatives for a PQM system.
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Alhamzi, Ghaliah, Saman Javaid, Umer Shuaib, Abdul Razaq, Harish Garg, and Asima Razzaque. "Enhancing Interval-Valued Pythagorean Fuzzy Decision-Making through Dombi-Based Aggregation Operators." Symmetry 15, no. 3 (2023): 765. http://dx.doi.org/10.3390/sym15030765.
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The success of any endeavor or process is heavily contingent on the ability to reconcile and satisfy balance requirements, which are often characterized by symmetry considerations. In practical applications, the primary goal of decision-making processes is to efficiently manage the symmetry or asymmetry that exists within different sources of information. In order to address this challenge, the primary aim of this study is to introduce novel Dombi operation concepts that are formulated within the framework of interval-valued Pythagorean fuzzy aggregation operators. In this study, an updated score function is presented to resolve the deficiency of the current score function in an interval-valued Pythagorean fuzzy environment. The concept of Dombi operations is used to introduce some interval-valued Pythagorean fuzzy aggregation operators, including the interval-valued Pythagorean fuzzy Dombi weighted arithmetic (IVPFDWA) operator, the interval-valued Pythagorean fuzzy Dombi ordered weighted arithmetic (IVPFDOWA) operator, the interval-valued Pythagorean fuzzy Dombi weighted geometric (IVPFDWG) operator, and the interval-valued Pythagorean fuzzy Dombi ordered weighted geometric (IVPFDOWG) operator. Moreover, the study investigates many important properties of these operators that provide new semantic meaning to the evaluation. In addition, the suggested score function and newly derived interval-valued Pythagorean fuzzy Dombi aggregation (IVPFDA) operators are successfully employed to select a subject expert in a certain institution. The proposed approach is demonstrated to be successful through empirical validation. Lastly, a comparative study is conducted to demonstrate the validity and applicability of the suggested approaches in comparison with current techniques. This research contributes to the ongoing efforts to advance the field of evaluation and decision-making by providing novel and effective tools and techniques.
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Marsili-Libelli, S., A. Spagni, and R. Susini. "Intelligent monitoring system for long-term control of Sequencing Batch Reactors." Water Science and Technology 57, no. 3 (2008): 431–38. http://dx.doi.org/10.2166/wst.2008.133.
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This paper discusses the application of artificial intelligence (AI) concepts to the monitoring of a lab-scale Sequencing Batch Reactor (SBR) treating nitrogen-rich wastewater (sanitary landfill leachate). The paper describes the implementation of a fuzzy inferential system to identify the correct switching sequence of the process and discusses the results obtained with six months of uninterrupted operation, during which the process conditions varied widely. The monitoring system proved capable of adjusting the process operation, in terms of phase length and external COD addition, to the varying environmental and loading conditions, with a percentage of correct phase recognition in excess of 95%. In addition, the monitoring system could be remotely operated through the internet via TCP/IP protocol.
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Guo, Jianpeng, Zemin Lu, Bingbo Cui, and Yuanzhen Xie. "Design and Test of Adaptive Leveling System for Orchard Operation Platform." Sensors 25, no. 5 (2025): 1319. https://doi.org/10.3390/s25051319.
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When the orchard operation platform is in use within the orchard, issues of tilting and overturning can arise due to uneven ground, necessitating instant leveling. In this study, the orchard operation platform is simplified into a four-point leveling mechanism, and an adaptive leveling system based on an inertial measurement unit (IMU) is designed. The relationship between coordinate transformation is utilized to derive the platform tilt angle and the position error relationship of the electric actuator, allowing for the analysis of the angle adjustment factors of the leveling mechanism. Through co-simulation using MATLAB and ADAMS, fuzzy control is implemented in addition to PID control, resulting in improved performance. A prototype model of the orchard operation platform is produced and tested, with the platform’s attitude angle remaining stable within a range of ±1.5°. The average leveling time is found to be within 3.6 s. The mean values of dynamic leveling inclination under PID and fuzzy PID control are 2.6° and 1.6°, respectively, with corresponding standard deviations of 1.4° and 0.8°. It conforms to the development trend of agricultural machinery electrification and intelligence and provides a reference basis for manufacturers.
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Tang, Fang. "High-Performance Computational Early Warning Analysis of Agricultural Economy Relying on Binary Fuzzy Cluster Analysis Algorithm." Journal of Mathematics 2021 (November 23, 2021): 1–13. http://dx.doi.org/10.1155/2021/4281415.
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In this paper, a binary fuzzy cluster analysis algorithm is used for an in-depth study and analysis of high-performance computational early warning in the agricultural economy. The definition of interval type-two fuzzy set and its operation are summarized. Considering the uncertain information that will be encountered in the evaluation process, this paper constructs the evaluation model of rural informatization construction performance based on interval type-two fuzzy numbers, which improves the accuracy of the evaluation results. The fuzzy clustering centres are modified according to the nature of the fuzzy clustering centre matrix, and the optimal fuzzy clustering centres and optimal fuzzy clustering division matrix with consistent order are solved. Using the level eigenvalues to find out in the abundant water period, there are 4 monitoring sections of water quality evaluation results for still clean and 5 monitoring sections of water quality evaluation results for slight pollution. In the flat-water period, there are 2 monitoring sections of the water quality evaluation results that are still clean and 7 monitoring sections of the water quality evaluation results are slightly polluted. In the dry water period, the water quality evaluation results of the 9 monitoring sections are slightly polluted. The results and the use of integrated pollutant index evaluation method results are consistent, indicating that the use of fuzzy clustering model for water quality evaluation is practical and effective. Its functional structure includes management business, innovation business, service business, production business, and operation business functions, in addition to the design of the collection and storage scheme based on Hadoop data warehouse, to achieve accurate matching of information of science and technology agricultural services in the whole agricultural industry chain. Finally, the implementation and maintenance of the cloud-based science and technology agricultural service information system are deployed, and the operational effects of its information system-related functions are demonstrated using prototype design. This paper constructs a comprehensive information system for science and technology agricultural services based on cloud technology that integrates management, innovation, service, production, and operation, which meets not only the needs of traditional science and technology agricultural service information systems, such as expert consultation and training demonstration, but also other needs spawned by the development of agricultural modernization.
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Ali, Jawad, and Ahmad N. Al-kenani. "Vector Similarity Measures of Dual Hesitant Fuzzy Linguistic Term Sets and Their Applications." Symmetry 15, no. 2 (2023): 471. http://dx.doi.org/10.3390/sym15020471.
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The dual hesitant fuzzy linguistic term set (DHFLTS) is defined by two functions that express the grade of membership and the grade of non-membership using a set of linguistic terms. In the present work, we first quote an example to point out that the existing complement operation of DHFLTS is on the wrong track. Meanwhile, we redefine this operation to fill the holes in the existing ones. Next, the notion of information energy under a dual hesitant fuzzy linguistic background is provided in order to build the criteria weight determination model. To further facilitate the theory of DHFLTS, we propose two vector similarity measures, i.e., Jaccard and Dice similarity measures, and their weighted forms for DHFLTS. In addition, we pioneer some generalized similarity measures of DHFLTSs and indicate that the Dice similarity measures are particular instances of the generalized similarity measures for some parameter values. Afterward, the similarity measures-based model with unknown weight information under the background of dual hesitant fuzzy linguistic environment is constructed. Lastly, an illustrated example is included to validate the method’s application, along with sensitivity analysis and comparative analysis, demonstrating the practicality and validity of its results.
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Sun, Yi Yun, Xin Wang, Yi Hui Zheng, Li Xue Li, Li Dan Zhou, and Qing Shan Xu. "Risk Assessment of Power Transformer Based on FTA, FAHP and GA." Applied Mechanics and Materials 448-453 (October 2013): 2274–77. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2274.
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The reliability of power transformer is very important to the safe operation of the power system. So a new method for power transformer risk assessment based on FTA, FAHP and GA is proposed. The method firstly establishes the power transformer fault tree; Secondly, it analyzes the fault tree through Fuzzy Analytic Hierarchy Process and constructs the fuzzy judgment matrix on transformer fault factors; Finally, it changes the question of solving the weight coefficients of each factor into a mathematical programming problem, and uses Genetic Algorithms to get the result so as to obtain the transformer reliability. In addition, the application result shows the effectiveness of the method above.
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Wu, Kaili, Jingchun Feng, Sheng Li, Ke Zhang, and Daisong Hu. "Project Portfolio Selection Considering the Fuzzy Chance Constraint of Water Environmental Restoration." Water 15, no. 13 (2023): 2428. http://dx.doi.org/10.3390/w15132428.
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The water environment restoration project portfolio (WERP) selection is discussed in this paper. By complying with the analysis of the project’s multidimensional property and operation mode, this paper develops the chance constraint and the management constraint of the WERP from the perspectives of public service and enterprise operation. In addition, the multi-objective mixed integer linear programming model is constructed by combining the expectation method and the fuzzy chance constraint programming method. The results demonstrate that: (1) Our proposed method successfully circumvents the occurrence of local objective optimization within a specific confidence interval, thereby achieving a balance between economic and water environment restoration objectives; (2) including fuzzy chance constraints in our proposed method significantly diminishes the risk of exceeding the WERP capacity, thereby ensuring the effectiveness of water environment restoration by adopting a market-based approach. However, further examination of the impact of various sub-projects in WERP is necessary, along with the integration of novel evolutionary algorithms to enhance the efficiency of our model.
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Jiang, Xidi, Shuheng Zhong, and Jialu Liang. "Simulation of Unsafe Behavior in Mine Operation Based on the SMAPP Model." Processes 11, no. 6 (2023): 1732. http://dx.doi.org/10.3390/pr11061732.
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Mine accidents are mostly caused by human unsafe behavior. To reduce the unsafe behavior of mine operation and reduce the accident of mine operation, the main body of unsafe behavior ‘people’ is analyzed, and 24 attribute factors are selected from five aspects of people’s emotions, motivation, ability, personality, and pressure to construct the comprehensive model of human behavior SMAPP (sentiment–motivation–ability–personality–pressure). The program tool for recording, saving, and executing the mutual and interactive influence relationship of 24 attribute factors under different state values and the simulation process framework of SMAPP was constructed by using 1071 rule statements written in Python language. The fuzzy rules are used to simulate different scenarios. The simulation results are consistent with the actual research results, which shows the reliability and scientificity of the model. In addition, additional events are added to the simulation process to make the model more realistic. Through the simulation results, the influence of employees’ emotions, motivations, abilities, personalities, pressures, and additional events on the unsafe behavior of mine operations is analyzed and predicted, and the measures to reduce the unsafe behavior of mine operations are further proposed.
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Li, Ming Cheng, Ming Der Jean, Jyh Horng Chou, and Bor Tsuen Lin. "The Enhancement of Integrated Properties of WC-Co Coatings Fabricated Using an HVOF Spraying." Materials Science Forum 675-677 (February 2011): 541–45. http://dx.doi.org/10.4028/www.scientific.net/msf.675-677.541.
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This study reported on Taguchi-Fuzzy logic model with statistical experiments to characterize the tungsten carbide/cobalt (WC-Co) deposited quality properties of the high-velocity oxygen-fuel (HVOF) process. The eight control factors were designed in a factorial orthogonal array experiment, and the effects of control parameters on the integrated surface properties were critically evaluated in the Taguchi designed experiments. A fuzzy logic system with knowledge bases in the inference engine was used to explore the relationships between variables and responses in the modified structures. In addition, the structure and properties of HVOF sprayed WC-Co coating were reported. Furthermore, a confirmation experiment of the optimal process was conducted. It was clear that HVOF sprayed WC-Co coating estimations are greatly improved through the Taguchi-Fuzzy logic operation, and these findings achieved the desired values in the modified properties.
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Saleh, B. Al-Tuhaifi, and Mousa Al-Aubidy Kasim. "Neuro-fuzzy-based anti-swing control of automatic tower crane." TELKOMNIKA 21, no. 04 (2023): 891–900. https://doi.org/10.12928/telkomnika.v21i4.24044.
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Controlling the position of the final load and the anti-swing control of the loads during the operation of the tower crane are challenging tasks. These are the most important control issues for safe operation, which are difficult to achieve easily with conventional control systems. Hence, the need to integrate the concepts of soft-computing into the tower crane control system. The aim of this research work is to design an adaptive-network-based fuzzy inference system (ANFIS) controller to move the payload to the final position with the lowest possible swing angle. To evaluate the ability of the proposed controller to meet the control requirements, its performance was compared to three other controllers: a conventional proportional derivative (PD) controller, a fuzzy-tuned PD controller and a fuzzy controller. MATLAB-based computer simulations of the crane and controllers were carried out to verify and compare the performance of the proposed controllers. The obtained results show the effectiveness of the ANFIS-based controller in adjusting the load position while keeping the load fluctuations small at the final position. The load oscillation angle is about ±2.28° with the ANFIS controller while it is about ±10° when using the PD controller. In addition, only one ANFIS controller is used for both load position and swing angle control.
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Zaliatov, Artem, Roman Zakiria, Olena Berezshna, and Svetlana Malyhina. "Mathematical modeling of the vector control sys-tem of the asynchronous drive of the bridge crane with a fuzzy-controller for the purpose of increasing energy-efficiency." Bulletin of Kharkov National Automobile and Highway University 1, no. 104 (2024): 22. http://dx.doi.org/10.30977/bul.2219-5548.2024.104.1.22.
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The article solves the current scientific and technical problem of increasing the energy efficiency of the control system for asynchronous electric drives of lifting and transport equipment of enterprises in the engineering industry, in particular overhead cranes, characterized by a high level of dynamic load both in terms of mechanical and electromagnetic indicators. In order to compare the efficiency of control systems, computer modeling of vector control of an asynchronous electric drive was carried out using proportional-integral controllers and neuroregulators based on fuzzy logic. The results of the simulation are presented and the advantages of using a vector control system with a fuzzy neuroregulator in relation to an asynchronous electric drive of an overhead crane are shown, namely, increasing the energy efficiency of operation and reducing dynamic loads during sudden changes in the control signal, ensuring high accuracy of the control process. Goal. Study of the dynamics of an electric drive with a fuzzy controller to achieve improved energy efficiency indicators of material handling equipment. Methodology. An algorithm has been developed for the operation of a vector control system for an asynchronous electric drive of an overhead crane with a fuzzy controller. Computer models of electric drive vector control and vector control subsystems have been developed. A neuroregulator for a vector control system for an asynchronous drive of an overhead crane was synthesized. Results. Mathematical modeling of an electric drive with vector control and the use of proportional-integral and Fuzzy controllers in the electric drive speed loop showed the difference in dynamic modes. A system with a fuzzy controller shows better energy efficiency in transient processes. Power decrease is 15-20%. Conclusions. The simulation results indicate an increase in energy efficiency in transient processes when operating lifting and transport equipment with an asynchronous electric drive. In addition, the use of a fuzzy neuroregulator operating on the basis of Fuzzy logic in the control system makes it possible to create a high-precision asynchronous electric drive with smooth transient processes.
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Mustafa, Albara M., and Abbas Barabadi. "Criteria-Based Fuzzy Logic Risk Analysis of Wind Farms Operation in Cold Climate Regions." Energies 15, no. 4 (2022): 1335. http://dx.doi.org/10.3390/en15041335.
Full textAbstract:
Different risks are associated with the operation and maintenance of wind farms in cold climate regions, mainly due to the harsh weather conditions that wind farms experience in that region such as the (i) increased stoppage rate of wind turbines due to harsh weather conditions, (ii) limited accessibility to wind farms due to snow cover on roads, and (iii) cold stress to workers at wind farms. In addition, there are risks that are caused by wind farms during their operation, which impact the surrounding environment and community such as the (iv) risk of ice throw from wind turbines, (v) environmental risks caused by the wind farms, and (vi) social opposition risk to installing wind farms in cold climate regions, such as the Arctic. The analysis of these six risks provides an overall view of the potential risks encountered by designers, operators, and decision makers at wind farms. This paper presents a methodology to quantify the aforementioned risks using fuzzy logic method. At first, two criteria were established for the probability and the consequences of each risk; with the use of experts’ judgments, membership functions were graphed to reflect the two established criteria, which represented the input to the risk analysis process. Furthermore, membership functions were created for the risk levels, which represented the output. To test the proposed methodology, a wind farm in Arctic Norway was selected as a case study to quantify its risks. Experts provided their assessments of the probability and consequences of each risk on a scale from 0–10, depending on the description of the wind farm provided to them. Risk levels were calculated using MATLAB fuzzy logic toolbox and ranked accordingly. Limited accessibility to the wind farm was ranked as the highest risk, while the social opposition to the wind farm was ranked as the lowest. In addition, to demonstrate the effects of the Arctic operating conditions on performance and safety of the wind farm, the same methodology was applied to a wind farm located in a non-cold-climate region, which showed that the risks ranked differently.