Academic literature on the topic 'Fuzzy addition operation'
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Journal articles on the topic "Fuzzy addition operation"
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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.
Dissertations / Theses on the topic "Fuzzy addition operation"
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Ivana, Štajner-Papuga. "Uopštena konvolucija." Phd thesis, Univerzitet u Novom Sadu, Prirodno-matematički fakultet u Novom Sadu, 2001. https://www.cris.uns.ac.rs/record.jsf?recordId=5987&source=NDLTD&language=en.
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U ovoj tezi je definisana uopštena konvolucija koja pripada domenu pseudo-analize i ima veliku primenu u mnogim matematičkim teorijama, npr. u proba-bilističkim metričkim prostorima, PDJ, teorijama odlučivanja, sistema, kontrole i fazi brojeva. Dokazane su bitne osobine ove operacije sa funkcijama. Dokazana je veza izmedju pseudo-konvolucija baziranih na poluprstenima različitih klasa Definisana je (5, C/)-konvolucija bazirana na uslovno distributivnom poluprstenu ([0,1], S, U)).Dat je još jedan vid uopštenja konvolucije baziran na uopštenim pseudo-operacijama.<br>In this thesis the generalized convolution have been defined. This operation with functions has applications in different mathematical theo­ ries, for example in Probabilistic Metric Spaces, PDE, System and Control Theory, Fuzzy numbers. Some basic properties of this operation has been proved, as well as connection between generalized convolutions based on dif­ferent classes of semirings. (5, U)-convolution has been defined, as well as convolution based on generalized pseudo-operations.
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Chang, Feng-chang, and 張逢昌. "A study on the fuzzy numbers addition and subtraction operations." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/92035742828653007147.
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碩士<br>國立臺南大學<br>應用數學研究所碩士班<br>101<br>This research direction uses the addition, or the operation of subtraction in discussion of the fuzzy number addition and subtraction operation, and because of the Magistrate of fuzzy number several times function and - the cut set idea takes the fuzzy number addition, the subtraction operation, takes the most common triangle fuzzy number and trapezoidal fuzzy number as the main showing theme, how to make the addition, how to make the operation of subtraction? ; If two triangles make the fuzzy number addition, or makes the operation of fuzzy number subtraction, can be a triangle fuzzy number? ; Similarly, when two trapezoids also make the fuzzy number addition, or can the arithmetic operation of subtraction, be a trapezoidal fuzzy number? ; The findings discovered that so long as the fuzzy number with shape makes the addition, or makes the operation of subtraction, its operation result still for same shape fuzzy number, moreover its graph also still for same shape fuzzy number.
Book chapters on the topic "Fuzzy addition operation"
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Rommelfanger, Heinrich, and Tibor Keresztfalvi. "Fuzzy Linear Programming with T-Norm Based Extended Addition." In Operations Research Proceedings 1991. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-46773-8_125.
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Alizadeh, Akif V., Rashad R. Aliyev, and Oleg H. Huseynov. "Algebraic Properties of Z-Numbers Under Additive Arithmetic Operations." In 13th International Conference on Theory and Application of Fuzzy Systems and Soft Computing — ICAFS-2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04164-9_118.
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Rezaei Aderyani, Safoura, Reza Saadati, Chenkuan Li, and Tofigh Allahviranloo. "Multi Stability of Pseudo Stochastic Additive Fuzzy Operator Inequalities in MVFB–Algebras." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55564-0_18.
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Rezaei Aderyani, Safoura, Reza Saadati, Chenkuan Li, and Tofigh Allahviranloo. "Multi Stability of Pseudo Stochastic Tri–Additive Fuzzy Operator Inequalities in MVFC–$$\diamond $$–Algebras." In Studies in Systems, Decision and Control. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55564-0_16.
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Sharma, B., A. Sikka, J. Lautze, and Tafadzwanashe Mabhaudhi. "Management and Agricultural Water Productivity Improvement in India and The Ganges Basin." In Enhancing Water and Food Security Through Improved Agricultural Water Productivity. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1848-4_3.
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Abstract The fast transition of India from a water-stressed to a water-scarce country has provided additional impetus for the search for interventions and decision support systems (DSSs) for solutions to problems arising from a mismatch between demand and supply and competing demands of economic and environmental sectors. Agriculture is the largest user of freshwater and increasing water productivity in agriculture is a national challenge requiring urgent attention. Globally, DSSs have gained immense popularity in various domains and, more recently, in agriculture and water resources management but are still limited in developing countries like India. This chapter presents a comprehensive compilation and stocktake of the DSSs developed at various scales in India and specific to the Ganges Basin, aimed at serving as a foundation for future work in this direction. After the criteria-based screening of the literature and reports, each selected DSS was analysed in the context of the aspects covered, key criteria, and the parameters such as relevance, applicability, focus, and scale of application. To reinforce the recommendations, KIIs were held with selected experts and stakeholders. A matrix approach was employed to compile and review the DSS with broader segregation under (i) crop and farm-based decision support systems, (ii) DSS based on artificial intelligence, enhanced machine learning, fuzzy multi-criteria decision making, and knowledge systems, (iii) DSS for real-time operation of micro-irrigation systems, (iv) DSS for management of tanks and reservoirs for water-deficit regions, and (v) DSS for improving water productivity under canal commands and conjunctive management of surface and groundwater resources. The selected DSSs were then analysed for focus, key findings, relevance, applicability, and scale of application of the DSS.
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Zhang, Chaohong, Xingguang Geng, Jun Zhang, Yunfeng Wang, and Yitao Zhang. "The Processing Method of Wrist Radial Artery Ultrasonic Signal Based on CORDIC Algorithm." In Fuzzy Systems and Data Mining IX. IOS Press, 2023. http://dx.doi.org/10.3233/faia231013.
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The human wrist radial artery is rich in important physiological and pathological information. The rapid dynamic detection of radial artery can be realized by ultrasonic imaging method. Because of the small amplitude fluctuation and narrow vessel width of the wrist radial artery, it is difficult to detect the vessels by ultrasound. In ultrasonic nondestructive testing system, CORDIC algorithm can realize complex operation only through simple addition, subtraction and shift transformation. It has obvious advantages in high-speed operation, especially suitable for optimizing ultrasonic signal processing algorithm. Based on CORDIC algorithm, this paper proposes a phased array ultrasonic signal processing method for wrist radial artery. The dynamic filtering, orthogonal demodulation and logarithmic compression techniques using CORDIC algorithm are mainly studied. FPGA simulation results show that CORDIC algorithm can realize the rapid reproduction of the wrist radial artery ultrasonic echo signal, which lays the foundation for the next step of the interpretation of the physiological and pathological information on the radial artery.
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Mutovkina, Nataliya. "Fuzzy Assessment of the Effectiveness of Innovative Projects in Industry." In Advances in Transdisciplinary Engineering. IOS Press, 2023. http://dx.doi.org/10.3233/atde231031.
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The innovative activity of industrial enterprises is the key to their successful operation and maintaining competitiveness in the market. The useful of innovations in product manufacturing technology, as well as in the management and control system, allows not only to maintain competitive positions but also to strengthen them. However, any innovative activity requires financial investments. Assessing the expediency of these investments, ensuring the possibility of comparing the planned results with the costs of innovation, is a problematic area of this work. Despite the certain development and proposals of solutions in this area, the problem of accurate assessment of the effectiveness of innovations remains relevant. This is important to the specifics of industrial enterprises, their industry affiliation, financial and other capabilities. As practice and set publications on this topic show, there is no single method for evaluating the effectiveness of innovations. The decision to invest in innovation is influenced by many factors that are different for each business entity. Most owners and managers, when evaluating innovative projects, solve the problem of choice, relying on traditional methods of calculating performance indicators and considering an innovative project as an investment. Such methods include calculations of net discounted income, internal rate of return, payback period of the project, profitability index, and other indicators. However, when using these methods, the qualitative effects of the introduction and application of innovations are not taken into account. In addition, the quantitative effects expected from the use of innovations are also predictive values evaluated by experts. Accordingly, there is always a possibility that these effects will not be obtained. Decision making on the investment of an innovative project becomes more complicated if we are talking about several projects. Then making a decision that reduces to a binary value (the project is accepted/the project is rejected) turns into a choice task. Such a problem is characterized by a larger dimension, therefore, an increased complexity of the solution. The more alternatives, the higher the difficulty (the harder the choice). The article proposes a method for fuzzy evaluation of the effectiveness of innovative projects in industry, which is based on the formation of a system of linguistic expert rules. This system is being developed based on the results of active work with experts in industrial innovation and represents a fuzzy knowledge base. As a criterion for the effectiveness of such a system, the level of consistency of the solutions proposed by the system with expert assessments of the effectiveness of an innovative project serves. If the system shows results that are practically indistinguishable from the results issued by the expert group, then a decision is made on its operation.
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Balluff, Stefan, Jörg Bendfeld, and Stefan Krauter. "Meteorological Data Forecast using RNN." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch050.
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Gathering knowledge not only of the current but also the upcoming wind speed is getting more and more important as the experience of operating and maintaining wind turbines is increasing. Not only with regards to operation and maintenance tasks such as gearbox and generator checks but moreover due to the fact that energy providers have to sell the right amount of their converted energy at the European energy markets, the knowledge of the wind and hence electrical power of the next day is of key importance. Selling more energy as has been offered is penalized as well as offering less energy as contractually promised. In addition to that the price per offered kWh decreases in case of a surplus of energy. Achieving a forecast there are various methods in computer science: fuzzy logic, linear prediction or neural networks. This paper presents current results of wind speed forecasts using recurrent neural networks (RNN) and the gradient descent method plus a backpropagation learning algorithm. Data used has been extracted from NASA's Modern Era-Retrospective analysis for Research and Applications (MERRA) which is calculated by a GEOS-5 Earth System Modeling and Data Assimilation system. The presented results show that wind speed data can be forecasted using historical data for training the RNN. Nevertheless, the current set up system lacks robustness and can be improved further with regards to accuracy.
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Galindo, Jose, Angelica Urrutia, and Mario Piattini. "FSQL." In Fuzzy Databases. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-324-1.ch007.
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The SQL language was essentially developed by Chamberlin and Boyce (1974) and Chamberlin et al. (1976). In 1986, the American National Standard Institute (ANSI) and the International Standards Organization (ISO) published the standard SQL-86 or SQL1 (ANSI, 1986). In 1989, an extension of the SQL standard, called SQL-89, was published, and SQL2 or SQL-92 was published in 1992 (ANSI, 1992). SQL2 basically provided new types, constraints (such as checks or unique predicates), it supported subqueries in UPDATE and DELETE operations, and in the FROM clause, operator IN, ANY and ALL, CASE constructor, JOIN, UNION, INTERSECT and EXCEPT operators and the modification of base table through views. In the latest version of SQL standard, SQL 2003, major improvements have been made in a number of key areas. Firstly, it has additional object-relational features, which were first introduced in SQL-1999. Secondly, SQL 2003 standard revolutionizes SQL with comprehensive OLAP features and data-mining applications. Thirdly, SQL 2003 integrates popular XML standards into SQL (SQL/XML). Finally, numerous improvements have been made throughout the SQL 2003 standard to refine existing features.
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Kumar, Manoj, Jyoti Raman, and Priya Singh. "A Possibility Approach for the Single Item Lot Sizing Problem with Fuzzy Parameters." In Advances in Logistics, Operations, and Management Science. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9888-8.ch006.
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The main objective of this chapter is to deal with a single item lot sizing problem with fuzzy parameters, which is called the fuzzy single item lot sizing problem (F-SILSP). Since F-SILSP does not meet the crisp deterministic assumption, it cannot be solved by traditional mathematical programming. In this chapter, the possibility approach is chosen to convert the fuzzy model to be an equivalent crisp single item lot sizing problem (EC-SILSP). The equivalent crisp model from this transformation procedure is in the form of mixed integer linear programming (MILP). It can be solved by traditional solver to find an optimal solution for each pre-specified possibility level. A numerical example with both trapezoidal and triangular fuzzy parameters is illustrated to demonstrate that an equivalent crisp model can be used. In addition, the equivalent crisp model is employed in inventory planning in a case study of inventory planning for bituminous coal with trapezoidal fuzzy demand and triangular fuzzy unit price in a power plant of an example petrochemical company (Supreme Petro, India).
Conference papers on the topic "Fuzzy addition operation"
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Yang, Hedong, and Clark C. Guest. "Optical Implementation of Min and Max Operation." In Optical Computing. Optica Publishing Group, 1987. http://dx.doi.org/10.1364/optcomp.1987.me7.
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In fuzzy logic [1,2] and fuzzy cognitive maps (FCM) [3-5], the operations of maximum and minimum play roles that are parallel to those played by addition and multiplication in ordinary matrix algebra. For example, in a fuzzy associative memory (FAM) [6], the connection matrix is constructed by taking the outer product of the vector to be memorized with min operation substituting for product of elements, i.e, tij = min (ai, aj).
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Salmenpera¨, Pekka, and Juha Miettinen. "Supervised Operation Monitoring and Control System of Rotating Rolls." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55149.
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The dynamic behavior of rotating machinery depends on the construction and foundation of the machine and in addition of the machine running parameters. By choosing appropriate parameters it is possible to influence considerably on the vibration of the machine. By driving the machine in that kind of an advantageous running window it is possible to minimize the vibration of the machine and to improve the quality of the product, but not to lose the efficiency of the productivity. Machines where the running window is important in maximizing the quality of the product are rotating cylindrical rolls in line contact for example in paper machines and grinding machines. In that kind of machines resonance situations are the most dangerous operation situations. The on-line measurement from rotating machine components requires wireless measurement data transfer applications. Sophisticated systems for that purpose need transfer capacity of several channels and two-way communications. Two-way communications allows the control of the measurement, versatile analysis of measurement signals and the control or supervised control of the running situation of the machine. If network solutions, for example via www are used, it is possible to use remote operation monitoring and control. In this paper a supervised operation monitoring and control system of a pilot roll station at Tampere University of Technology is described. The main components of the system are measurement unit on the end flange of the rotating roll, wireless local area network for measurement data transfer from the rotating roll to the control room computer and the local area network that connects the process control and signal analysis computers together. The system contains also a WWW-based remote control system for measurement signals from the rotating rolls and for the process variables. One possibility in this kind of complicated control situation is to use the fuzzy logics principle. Fuzzy logics are principally suitable for process control when knowledge-based systems fit well in diagnostics. However, fuzzy rule-based control can be defined as a knowledge-based system. For finding out the suitable running windows in the pilot roll station a fuzzy rule-based, supervised roll rotational speed control system is used. The paper describes also the fuzzy systems and comprises preliminary experimental results.
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Zhang, Weiguo, Fuhai Duan, Zhong Zhao, and Xiangzhong Yang. "An Improved Fuzzy Integration Control Method Without Quantification." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8398.
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Abstract In this paper, dynamic inversion method is used to decouple a multivariable system. Then by canceling traditional fuzzy quantification operation and based on analytical optimal correction function and on-line interpolation, two improved design methods for fuzzy controllers are provided. A class of nonlinear PID controllers is formed when traditional PI controllers are joined after the improved fuzzy controllers immediately. Both methods can essentially remove the system’s steady-state errors and flutter phenomenon, which are caused by the fuzzy quantification errors and regulating dead bands in the traditional fuzzy control system. Finally, by combining the improved fuzzy control methods with the dynamic inversion method, a kind of dynamic decoupling fuzzy integration control method for multivariable systems is constructed. The integration control system designed by this method possesses not only excellent decoupling results and better control performance, but also stronger adaptability to the parameter changes in the system. In addition, an example and its simulation results are also provided.
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Benjamin, D., H. Gholam Hosseini, A. Al-Jumaily, and M. J. Harrison. "Fuzzy Logic Approach to Wireless Diagnostic Alarms in Anesthesia." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67058.
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This paper explores the use of a fuzzy logic system to continuously monitor a patient’s vital signs during an operation under anesthesia and evaluate the patient’s physiological state. The proposed systems aims to employ statistical-based alarms, principal component analysis (PCA) together with respiratory associated arterial pressure variation (Pulse Pressure Variation-PPV and Systolic Pressure Variation-SPV) and a new fuzzy logic model to estimate the physiological state of the patient under anesthesia. The fuzzy approach will include the recursive fuzzy inference system (RFIS) which combines the current patient status data with the previous output of the inference system thereby reinforcing the current finding based on previous sequential outputs. In addition to this, work is also aimed at the creation of a wireless module that will provide patient information directly to the system.
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Pinzón, Horacio, Cinthia Audivet, Javier Alexander, Melitsa Torres, Marlon Consuegra, and Marco E. Sanjuán. "A Novel Hybrid Strategy for Multimode Operation Mapping and Feature Extraction on Data-Driven Statistical Fault Detection Methods." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87417.
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Fault detection and diagnosis schemes based on data-driven statistical modelling are highly dependent on an accurate and exhaustive feature extraction procedure to deliver a superior performance as a monitoring strategy. Otherwise conducted, a deficient feature extraction procedure leads to a monitoring structure widely deviated from normal operating conditions. If an operating state is not identified as it, an increment in false alarm rate would be evidenced whenever the process shifts towards that condition and the monitoring scheme triggers the abnormal condition warning. On the other hand, if two similar operating conditions could not be individualized i.e. to be identified as a single operating state, a lack of sensitivity for minor — yet typical — deviations would render a monitoring strategy with prominent misdetection rates. Although Multimode Operational Mapping requires the proper identification of a finite set of normal process states, it is a challenging task especially for large-scale systems. Its complexity derives from a broad universe of monitoring variables, highly interactuating process units integrated over very dynamic network systems, among others. This is the case of natural gas transmission infrastructure, as it deals with variable upstream production rates, diverse consumption trends from customers, internal processes constrains, merged in a stringent operating scheme. This paper proposes a novel strategy to address the identification and feature extraction of normal conditions on multimode operation systems. The proposed framework uses a segmentation approach based on operator’s knowledge, the Takagi-Sugeno-Kang fuzzy engine and k-means algorithm to characterize the normal operation states of the system. The results show an improvement in the performance of Principal Component Analysis during abnormal conditions detection, in addition an increase on the sensitivity of Hotelling and Q statistics.
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Xie, Shuyi, Shaohua Dong, and Guangyu Zhang. "Identification of Key Factors of Fire Risk of Oil Depot Based on Fuzzy Clustering Algorithm." In ASME 2019 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/pvp2019-93125.
Full textAbstract:
Abstract With the rapid development of the national economy, the demand for oil is increasing. In order to meet the increasing energy demand, China has established a number of oil depot in recent years, whose largest capacity reaching up to tens of millions of cubic meters. Due to the flammable and explosive nature of the stored medium, the risk of fire in the oil depot area has increased dramatically as the tank capacity of the storage tank area has increased. The intensification of the oil depot and the development of large-scale oil storage tanks have brought convenience to the national oil depot, but also brought many catastrophic consequences. In recent years, there have been many fires and explosions in the oil depot, causing major casualties and property losses, which seriously endangered the ecological environment and public safety. Based on the constructed oil depot fire risk index system, the fuzzy C-means algorithm (FCM) and fuzzy maximum support tree clustering algorithm is introduced. Through the two fuzzy clustering mathematical models, key factors in the established index system are identified. Firstly, the expert scoring method is used to evaluate the indicators in the oil depot fire risk index system, and the importance degree evaluation matrix of oil depot fire risk factors is constructed through the fuzzy analysis of expert comments. Then, the fuzzy C-means algorithm (FCM) and the fuzzy clustering tree algorithm are used to cluster the various risk indicators, and the key factors of the oil depot fire risk are identified. Through the comparative analysis and cross-validation of the results of the two fuzzy clustering methods, the accuracy of the recognition results is ensured. Finally, using an oil depot as a case study, it is found that passive fire prevention capability and emergency rescue capability are key factors that need to be paid attention to in the oil depot fire risk index. The fuzzy clustering algorithm used in this paper can digitize the subjective comments of experts, thus reducing the influence of human subjective factors. In addition, by using two fuzzy clustering algorithms to analyze and verify the key factors of the oil depot fire risk, the reliability of the clustering results is guaranteed. The identification of key factors can enable managers to predict high-risk factors in advance in the fire risk prevention and control process of the oil depot, so as to adopt corresponding preventive measures to minimize the fire risk in the oil depot, and ensure the safety of the operation of the oil depot.
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Jung, Soonmoon, Jaemin Kim, Youngho Lee, et al. "A Study on the Development of an Automatic Circular Anastomosis Stapler with a Fuzzy Control Algorithm." In 2025 Design of Medical Devices Conference. American Society of Mechanical Engineers, 2025. https://doi.org/10.1115/dmd2025-1024.
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Abstract Anastomosis is a surgical operation performed to connect intra-abdominal organs. The circular anastomosis stapler, which is commonly used in anastomosis, is used to connect the separated intestine due to cancer removal. The organs of the human body have different thicknesses and properties for each person; different anastomosis intervals should be applied for each patient. However, the existing circular stapler determines the anastomosis interval only through manual displacement control without considering the anatomical location, structure, and compression pressure of the abdominal organs, which leads to side effects such as leakage and necrosis at the anastomosis site. Therefore, in this study, we developed an automatic circular anastomosis stapler using a strain gauge, an electric motor, and a microcontroller equipped with a fuzzy control algorithm. The developed automatic circular anastomosis stapler provides the optimal anastomosis interval by utilizing and analyzing the mechanical properties and pressure of the large intestine. In addition, the Head-Neck part was designed to be replaceable, and the Handle part, which oversees the motor and control, was manufactured to be reusable.
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Kong, Changduk, Semyeong Lim, and Keonwoo Kim. "Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-68158.
Full textAbstract:
Recently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks, Fuzzy Logic and Genetic Algorithms have been studied to improve the model based engine diagnostic methods. Among them the Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if only use of the Neural Networks. In addition, it has a very complex structure due to finding effectively faults of single type faults and multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP(Feed Forward Back Propagation) is used. In order to user’s friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB. The proposed program is verified by application of several case studies having the arbitrary implanted engine component faults as well as real engine performance data.
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Chen, Guo, Hong Xiao, Li Zhou, and Rui You. "Prediction of High-Speed Hydraulic Dynamometer Safety Envelope Base on Deep Learning Neural Network." In ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/gt2024-124927.
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Abstract High-speed hydraulic dynamometer is widely used for turbine component experiment in aircraft engine area. It usually works through measuring main performance parameters of turbine for verifying design method by absorbing huge shaft work which is passed from turbine. However, its water flow can generate strong turbulence phenomena between impellers in dynamometer’s case. In addition, high water temperature may generate cavitation phenomenon and cause high-frequency pressure pulsation. Both can lead to dynamometer’s performance degradation. Artificial experience diagnosis, though not suggested, is used commonly to prevent high-speed hydraulic dynamometer from working unsteadily. This method depends on the experience of workers, which may cause fuzzy definition and lead to safety hazard. In this paper, we propose a two-stage model of highspeed hydraulic dynamometer based on deep learning neural network. It utilizes the ideas of Transformer Model, which makes our model become more sensitive and stable. Accuracy and stability are proved by verifying actual device operation data. Based on two-stage model, we can draw work safety envelope by predicting performance parameters that delimit the safety boundary. Follow this guide workers can be able to make operation safer and stabler.
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Lin, Y. J., T. Lee, and D. Saravanos. "Relative Index Method for Nonlinear Strain Analysis of Piezoceramic Sensored Structure." In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0863.
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Abstract In this paper, a relative index method is proposed to analyze the nonlinear Von Karman strain effects on the piezoceramic sensored rotor blades. Although other qualitative and quantitative methods are available for nonlinear strain analysis, these methods have inherent drawbacks. For qualitative method the fuzzy terms such as severe, negligible influence, etc., are usually used to describe the effect. The main disadvantage of using these terms is that to different people the same fuzzy word can be interpreted differently. This causes inconsistency which may lead to inaccurate analysis. For quantitative methods, the major disadvantage is that they are unable to delineate the whole picture of the nonlinear effects. However, the proposed relative index method circumvents the drawbacks of both qualitative and quantitative methods. Firstly, it measures the nonlinear effect and converts it into a numerical value. The value is in the range of zero to one in which zero is corresponding to negligible effects and one indicates the highest severity of the nonlinear effects. In addition, to generate the index value this method takes the whole picture of nonlinear effect response into consideration. The results of using the relative index method show that at any given mode of vibration the nonlinear effect on sensor is relatively negligible at high rate of rotation than that on lower ones. The results also indicate that the nonlinear effect is increasing at lower modes of vibration but its effect on sensor almost levels off at higher modes. Moreover, if comparing index value of a given modes of vibration with the index value of its preceding modes, the effect of nonlinearity is decreasing. In addition, the results also suggest that at any given instantaneous speed of rotation the level of the nonlinear effect is diminishing with the higher acceleration/deceleration rate of operation of the blade.
Reports on the topic "Fuzzy addition operation"
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Wan, Wilfred, and Nivedita Raju. Escalation Risks at the Space–Nuclear Nexus. Stockholm International Peace Research Institute, 2024. http://dx.doi.org/10.55163/fzdw6296.
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Space systems are essential for nuclear and non-nuclear missions for China, Russia and the United States, with the space domain central in their national security strategies. Amid the strategic competition and rivalry between the three states, their threat perceptions exhibit unprecedented levels of worst-case scenario thinking, signalling a preparedness to respond with force in case of attacks or incidents involving space systems. Escalation risks in outer space, even possibly extending to the use of nuclear weapons, thus appear to be growing, especially as the deterrent role of such weapons is expanding to account for more capabilities with strategic effect. While different variables will impact escalation dynamics at the intersection of outer space, nuclear weapons and related systems (the ‘space–nuclear nexus’), some factors clearly contribute to the risk of escalation. These include strategic ambiguity and unclear red lines on what actions could result in potential nuclear retaliation. These fuzzy red lines are further blurred by the many uncertainties in space operations, such as congestion of orbits, considerations of potential civilian harm, the role of commercial actors in space, and the integration of artificial intelligence into space systems. Additional space–nuclear-related risk reduction measures are therefore vital. This paper proposes measures at the multilateral, bilateral and unilateral levels for China, Russia and the USA to consider.