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Journal articles on the topic 'Fuzzy relational concept analysis'
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Boffa, Stefania, Petra Murinová, and Vilém Novák. "A proposal to extend Relational Concept Analysis with fuzzy scaling quantifiers." Knowledge-Based Systems 231 (November 2021): 107452. http://dx.doi.org/10.1016/j.knosys.2021.107452.
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De Maio, C., G. Fenza, M. Gallo, V. Loia, and S. Senatore. "Formal and relational concept analysis for fuzzy-based automatic semantic annotation." Applied Intelligence 40, no. 1 (2013): 154–77. http://dx.doi.org/10.1007/s10489-013-0451-7.
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Nobuhara, Hajime, and Kaoru Hirota. "A Fuzzification of Morphological Wavelets Based on Fuzzy Relational Calculus and its Application to Image Compression/Reconstruction." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 4 (2004): 373–78. http://dx.doi.org/10.20965/jaciii.2004.p0373.
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A new style of fuzzy wavelets is proposed by the fuzzification of morphological wavelets. Due to the correspondence of the morphological wavelets operations and fuzzy relational ones, wavelets analysis/synthesis schemes can be formulated based on fuzzy relational calculus. To enable efficient image compression/reconstruction, the concept of the alpha-band which is an alpha-cut generalization, is also proposed for thresholding wavelets. In an image compression/reconstruction experiment using test images extracted from the Standard Image DataBAse (SIDBA), it is confirmed that the root mean square error (RMSE) of the proposed soft thresholding is decreased to 87.3% of conventional hard thresholding, when the original image is "Lenna."
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ALCALDE, CRISTINA, ANA BURUSCO, and RAMÓN FUENTES-GONZÁLEZ. "ANALYSIS OF CERTAIN L-FUZZY RELATIONAL EQUATIONS AND THE STUDY OF ITS SOLUTIONS BY MEANS OF THE L-FUZZY CONCEPT THEORY." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20, no. 01 (2012): 21–40. http://dx.doi.org/10.1142/s021848851250002x.
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Given a Brouwerian complete lattice (L,≤) and two referential sets K and E, and using a fuzzy relation R ∈ LE×E which is reflexive and symmetric, certain fuzzy relations [Formula: see text] are characterized as solutions of X ⊲ R = X, proving that they play the role of the blocks in the context of crisp tolerance relations. Moreover, it is verified that these new fuzzy blocks [Formula: see text] can be determinated by means of the L-fuzzy concepts associated with the K -labeled L-fuzzy context (L,K,E,E,R).
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Močkoř, Jiří. "Cut Systems with Relational Morphisms for Semiring-Valued Fuzzy Structures." Axioms 12, no. 2 (2023): 153. http://dx.doi.org/10.3390/axioms12020153.
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Many of the new MV-valued fuzzy structures, including intuitionistic, neutrosophic, or fuzzy soft sets, can be transformed into so-called almost MV-valued fuzzy sets, or, equivalently, fuzzy sets with values in dual pair of semirings (in symbols, (R,R*)-fuzzy sets). This transformation allows any construction of almost MV-valued fuzzy sets to be retransformed into an analogous construction for these new fuzzy structures. In that way, approximation theories for (R,R*)-fuzzy sets, rough (R,R*)-fuzzy sets theories, or F-transform theories for (R,R*)-fuzzy sets have already been created and then retransformed for these new fuzzy structures. In this paper, we continue this trend and define, on the one hand, the theory of extensional (R,R*)-fuzzy sets defined on sets with fuzzy similarity relations with values in dual pair of semirings and power sets functors related to this theory and, at the same time, the theory of cuts with relational morphisms of these structures. Illustratively, the reverse transformations of some of these concepts into new fuzzy structures are presented.
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Jiang, Xian-Ling, and Yi-Lin Zhao. "Grey Relational Method for Evaluating the Macro-Economy Performance with Triangular Fuzzy Information." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7385–89. http://dx.doi.org/10.1166/jctn.2016.5730.
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The new theory comes when the current economic circumstance cannot be explained. The Great Depression in 1930s severely smashed the world economy and no explanations and policies were provided by the classical laissez-faire until the Roosevelt New Deal took the world economy out of depression. The macroeconomic theory has been brought out by John Maynard Keynes. Early this century, not only did the US Sub-prime crisis strongly affect the world economy, but also the macroeconomic theory. The development of the macroeconomic theory after the Sub-prime crisis becomes a hot topic. In this paper, we investigate the multiple attribute decision making (MADM) problems for evaluating the macro-economy performance with triangular fuzzy information. Then, we extend the grey relational analysis (GRA) procedure for triangular fuzzy multiple attribute decision making for evaluating the macro-economy performance in triangular fuzzy setting. According to the concept of the GRA, a fuzzy relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of fuzzy grey relational coefficient to both the triangular fuzzy positive-ideal solution (TFPIS) and triangular fuzzy negative-ideal solution (TFNIS) simultaneously. Finally, an illustrative example for evaluating the macro-economy performance is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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Huang, Sue-Fen. "Cognitive diagnostic assessment based on knowledge structure." MATEC Web of Conferences 169 (2018): 01020. http://dx.doi.org/10.1051/matecconf/201816901020.
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The purpose of this study is to provide an integrated method of fuzzy theory basis for individualized concept structure analysis. In order to insight the misconception of learning basic mathematics and progress teaching. This method integrates Fuzzy Logic Model of Perception (FLMP) and Interpretive Structural Modelling (ISM). The combined algorithm could analyze individualized concepts structure based on the comparisons with concept structure of expert. In this paper, some well-known knowledge structure assessment methods will be discussed. For item connection, Bart et al ordering theory and Takeya’s item relational structure provided ordering coefficient to construct item relationships and hierarchies. For concepts or skills connection, Warfield’s ISM and Lin et al Concept Advanced Interpretive Structural Modelling (CAISM) provided to construct graphic relationship among elements and display the individualized concept hierarchy structure by numeric and picture. Samples contain 427 which come from Min-Hwei Junior College. Subjects were analyzed by CAISM. It shows the traditional assessment is not the only criteria; it must be combined with other assessment tools. The result shows that CAISM gives meaningful learning and lacks of learners.
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Wei, Qian. "Product Shape Design Scheme Evaluation Method Based on Spatial Data Mining." Mathematical Problems in Engineering 2022 (July 20, 2022): 1–8. http://dx.doi.org/10.1155/2022/3231357.
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The stage of product modeling design implies a lot of complex tacit knowledge, which is the embodiment of the design concept centered on product modeling design and is also the hot spot and difficulty of modern design theory and method research. Aiming at the evaluation and decision of product modeling design scheme, a decision-making method of approaching ideal solution ranking based on grey relational analysis was proposed, which realized the convergence of tacit knowledge. The empty association rule is an important knowledge content of spatial data mining. A fuzzy genetic algorithm can solve the characteristics of random and nonlinear problems and solve the data mining problems of spatial association rules. The fuzzy genetic algorithm of discrete crossover probability and mutation probability is applied to data mining of spatial association rules in a spatial database, the coding method of the fuzzy genetic algorithm and the construction of fitness function are discussed, and the process of mining spatial association rules is given. The results show that the method of mining s association rules with the fuzzy genetic algorithm is feasible and has higher mining efficiency. This paper discusses the construction method of designing a decision support database based on linear regression and neural network and then proposes a decision method combining TOPSIS and grey relational analysis, which comprehensively considers the position and shape of the scheme data curve.
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Riaz, Muhammad, Muhammad Tahir Hamid, Deeba Afzal, Dragan Pamucar, and Yu-Ming Chu. "Multi-criteria decision making in robotic agri-farming with q-rung orthopair m-polar fuzzy sets." PLOS ONE 16, no. 2 (2021): e0246485. http://dx.doi.org/10.1371/journal.pone.0246485.
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q-Rung orthopair fuzzy set (qROFS) and m-polar fuzzy set (mPFS) are rudimentary concepts in the computational intelligence, which have diverse applications in fuzzy modeling and decision making under uncertainty. The aim of this paper is to introduce the hybrid concept of q-rung orthopair m-polar fuzzy set (qROmPFS) as a hybrid model of q-rung orthopair fuzzy set and m-polar fuzzy set. A qROmPFS has the ability to deal with real life situations when decision experts are interested to deal with multi-polarity as well as membership and non-membership grades to the alternatives in an extended domain with q-ROF environment. Certain operations on qROmPFSs and several new notions like support, core, height, concentration, dilation, α-cut and (α, β)-cut of qROmPFS are defined. Additionally, grey relational analysis (GRA) and choice value method (CVM) are presented under qROmPFSs for multi-criteria decision making (MCDM) in robotic agri-farming. The proposed methods are suitable to find out an appropriate mode of farming among several kinds of agri-farming. The applications of proposed MCDM approaches are illustrated by respective numerical examples. To justify the feasibility, superiority and reliability of proposed techniques, the comparison analysis of the final ranking in the robotic agri-farming computed by the proposed techniques with some existing MCDM methods is also given.
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Rybanov, Alexander Aleksandrovich. "A PRACTICAL METHOD FOR IMPLEMENTING FUZZY QUERIES FOR RELATIONAL DATABASES." Mathematics and Informatics LXV, no. 4 (2022): 379–92. http://dx.doi.org/10.53656/math2022-4-5-pra.
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Information systems that use databases are flexible to the extent that they allow users to request the data they need. SQL is limited to precise data processing and does not directly express fuzzy concepts of natural language. Therefore, giving SQL some flexibility can help users improve interaction with information systems without requiring them to learn a completely new language. The task of reducing the labor intensity of the process of integrating the mechanisms of fuzzy requests to existing information systems is urgent. The article shows the limitations of clear queries, considers various forms of fuzzy queries. Known approaches to implementing fuzzy queries to relational databases were analyzed. Provides a detailed analysis of fuzzy queries, as well as their conversion to standard SQL queries using MySQL. The proposed method for implementing the ability to work with fuzzy queries is based on expanding a clear database with stored functions, without changing the structure and composition of its tables. The advantages of the method are: increased readability and understanding of SQL queries; ease of integration with existing databases of information systems; flexible adjustment of the linguistic variable membership function in accordance with the needs of the database user. The application of the method is shown by the example of adapting a MySQL database. The proposed adaptation method can be widely used to implement fuzzy queries to databases of various DBMS that support work with stored functions.
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Рыбанов, А. А., and А. А. Силаев. "METHOD ADAPTION RELATIONAL DATABASES TO FUZZY QUERIES." Южно-Сибирский научный вестник, no. 4(44) (August 31, 2022): 74–80. http://dx.doi.org/10.25699/sssb.2022.44.4.005.
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Информационные системы, использующие базы данных, являются гибкими в той мере, в какой они позволяют пользователям запрашивать необходимые им данные. Язык SQL ограничен точной обработкой данных и не позволяет напрямую выразить нечеткие понятия естественного языка. Следовательно, придание SQL некоторой гибкости может помочь пользователям улучшить взаимодействие с информационными системами, не требуя от них изучения совершенно нового языка. Актуальной является задача снижения трудоемкости процесса интеграции механизмов нечетких запросов к уже действующим информационным системам. В статье показана ограниченность четких запросов, рассмотрены различные формы нечетких запросов. Проанализированы известные подходы к реализации нечетких запросов к четким реляционным базам данных. Представлен подробный анализ нечетких запросов, а также их преобразование в стандартные SQL-запросы с помощью MySQL. Предлагается метод реализации запросов к реляционным базам данных, объединяющий теорию нечетких множеств и SQL. Предлагаемый метод реализации возможности работы с нечеткими запросами основан на расширении четкой базы данных хранимыми функциями, без изменения структуры и состава ее таблиц. Преимуществами метода являются: повышение удобочитаемости и понимания SQL-запросов; простота интеграции с уже существующими базами данных информационных систем; гибкая настройка функции принадлежности лингвистических переменных в соответствии с потребностями пользователя базы данных. Применение метода показано на примере адаптации базы данных MySQL. Предложенный метод адаптации может быть широко использован для реализации нечетких запросов к базам данных различных реляционных СУБД, поддерживаюших работу с хранимыми функциями. Abstract – Information systems that use databases are flexible to the extent that they allow users to request the data they need. SQL is limited to precise data processing and does not directly express fuzzy concepts of natural language. Therefore, giving SQL some flexibility can help users improve interaction with information systems without requiring them to learn a completely new language. The task of reducing the labor intensity of the process of integrating the mechanisms of fuzzy requests to existing information systems is urgent. The article shows the limitations of clear queries, considers various forms of fuzzy queries. Known approaches to implementing fuzzy queries to relational databases were analyzed. Provides a detailed analysis of fuzzy queries, as well as their conversion to standard SQL queries using MySQL. The proposed method for implementing the ability to work with fuzzy queries is based on expanding a clear database with stored functions, without changing the structure and composition of its tables. The advantages of the method are: increased readability and understanding of SQL queries; ease of integration with existing databases of information systems; flexible adjustment of the linguistic variable membership function in accordance with the needs of the database user. The application of the method is shown by the example of adapting a MySQL database. The proposed adaptation method can be widely used to implement fuzzy queries to databases of various DBMS that support work with stored functions.
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Kuang, Qing. "Grey Relational Analysis Model for Comprehensive Evaluation on Risk Early-Warning for Enterprises Investment Project." Advanced Materials Research 748 (August 2013): 1267–72. http://dx.doi.org/10.4028/www.scientific.net/amr.748.1267.
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With the development of economic globalization and the rise of knowledge-based economy, human capital as the knowledge and skills of the carrier for the contribution of economic development has been more than other material capital, the competition between the enterprises also change correspondingly to talented person's competition, therefore, human capital has become the strategic resource of enterprise compete. However, human capital is different from other physical capital is the property that makes enterprise on the human capital investment is possessed of the potential huge risk. For enterprise speaking, how to identify, evaluate and prevent human capital investment risk to become the enterprise manpower management the important content in the work, has become the key to business success or failure. Therefore, further, thoroughly studies the enterprise human capital investment risk related theory is of great theoretical significance and practical significance. In this paper, we investigate the group decision making problems for evaluating the risk early-warning for enterprises investment project based on the grey relational analysis model with interval-valued intuitionistic fuzzy information. A modified GRA analysis method is proposed. Then, based on the traditional concept of GRA method, calculation steps for solving interval-valued intuitionistic fuzzy group decision-making problems are given. Finally, an illustrative example for evaluating the risk early-warning for enterprises investment project is given.
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Sahu, Santosh Kumar, Saurav Datta, and Siba Sankar Mahapatra. "Appraisement and benchmarking of supply chain performance extent." Grey Systems: Theory and Application 5, no. 1 (2015): 2–30. http://dx.doi.org/10.1108/gs-10-2014-0036.
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Purpose – Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making. Design/methodology/approach – This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent. Findings – In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly. Originality/value – Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.
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Liu, Chao, Guolin Tang, and Peide Liu. "An Approach to Multicriteria Group Decision-Making with Unknown Weight Information Based on Pythagorean Fuzzy Uncertain Linguistic Aggregation Operators." Mathematical Problems in Engineering 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/6414020.
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With respect to multicriteria group decision-making (MCGDM) problems in which the experts have different priority levels, the criteria values are in the form of Pythagorean fuzzy uncertain linguistic variables (PFULVs), and the information about weights of experts and criteria is completely unknown, a novel decision-making method is developed. Firstly, the concept of PFULV is defined, and some operational laws, score function, accuracy function, and normalized Hamming distance of PFULVs are presented. Then, to aggregate information given by all experts, the Pythagorean fuzzy uncertain linguistic prioritized weighted averaging aggregation (PFULPWAA) operator and the Pythagorean fuzzy uncertain linguistic prioritized weighted geometric aggregation (PFULPWGA) operator are proposed. Furthermore, in order to get a comprehensive evaluation value for each alternative, the Pythagorean fuzzy uncertain linguistic Maclaurin symmetric mean aggregation (PFULMSMA) operator and the weighted PFULMSMA (WPFULMSMA) operator are proposed. Moreover, to obtain the information about the weights of criteria, the model based on grey relational analysis (GRA) method is established. Finally, a method of MCGDM with PFULVs is developed, and an application example is given to illustrate the validity and feasibility of the provided procedure.
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Borisov, Vadim V., Sergey P. Kurilin, and Victor S. Luferov. "Fuzzy relational cognitive temporal models for analyzing and state prediction of complex technical systems." Journal Of Applied Informatics 17, no. 1 (97) (2022): 27–38. http://dx.doi.org/10.37791/2687-0649-2022-17-1-27-38.
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The effectiveness of fuzzy cognitive modeling methods for analyzing and predicting the state of complex technical systems (STS) is justified by the following reasons: significant interdependence, non-linear nature and incompleteness of information about the mutual influence of the analyzed parameters of the CTS; a variety of effects of internal and external factors on the CTS; complexity and cost of conducting experimental studies during the operation of these systems. The main limitations of fuzzy cognitive models for modeling STS dynamics are: the complexity of taking into account the mutual influence of parameters with their different time lags relative to each other; the need for their constant operational adjustment and training of component models for all parameters during the operation of the CTS. In this paper, Fuzzy Relational Cognitive Temporal Models (FRCTM) are developed. These models combine the advantages of various types of fuzzy cognitive models, and at the same time neutralize the main limitations of the analysis and prediction of the state of the CTS, which are inherent in the well- known fuzzy cognitive models. The paper also proposes models of system dynamics that take into account the specifics of the FRCTM. We have also developed an approach and implemented a method for calculating fuzzy dependencies in vector-matrix form for dynamic modeling of the CTS. The proposed method makes it possible to solve the problems of increasing the uncertainty of the results and the output of fuzzy values of the FRCTM concepts beyond the ranges of the base sets due to the execution of mass iterative computations. An example of modeling heterogeneous electromechanical systems based on FRCTM is given. The results obtained are the basis for solving a whole range of tasks of analysis, predictive evaluation, modeling of different scenarios of the functioning and development of heterogeneous electromechanical systems for various system factors, operating modes and external conditions.
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Ramesh, S., and L. Karunamoorthy. "Turning Investigations on Machining of Ti64 Alloy with Different Cutting Tool Inserts." Materials Science Forum 763 (July 2013): 1–27. http://dx.doi.org/10.4028/www.scientific.net/msf.763.1.
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Turning operation is fundamental in the manufacturing industry to produce cylindrical parts especially for producing near-nett shape, and aesthetic requirements with good dimensional accuracy. This present research chapter, an attempt has been made to investigate the machining characteristics of titanium alloys. The investigation has been carried out to measure the effect of tool flank wear, surface roughness, cutting force and temperature on different cutting tools by adopting Taguchi’s design of experiment concept. This investigation was set to analyse and develop a mathematical model using response surface methodology, fuzzy logic. The observed responses were optimized using grey relational grade algorithm. Except for a few cases, the experimental results have close proximity (95%) to the predicted value. This validates the model developed in this work. Orthogonal array with grey relational analysis has been successfully implemented for the optimization of the machining parameters. The optimized cutting conditions evolved in this research study will help to achieve better machinability of these advanced materials like titanium alloy.
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Abhishekh, Surendra Singh Gautam, and S. R. Singh. "A Score Function-Based Method of Forecasting Using Intuitionistic Fuzzy Time Series." New Mathematics and Natural Computation 14, no. 01 (2018): 91–111. http://dx.doi.org/10.1142/s1793005718500072.
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Intuitionistic fuzzy set plays a vital role in data analysis and decision-making problems. In this paper, we propose an enhanced and versatile method of forecasting using the concept of intuitionistic fuzzy time series (FTS) based on their score function. The developed method has been presented in the form of simple computational steps of forecasting instead of complicated max–min compositions operator of intuitionistic fuzzy sets to compute the relational matrix [Formula: see text]. Also, the proposed method is based on the maximum score and minimum accuracy function of intuitionistic fuzzy numbers (IFNs) to fuzzify the historical time series data. Further intuitionistic fuzzy logical relationship groups are defined and also provide a forecasted value and lies in an interval and is more appropriate rather than a crisp value. Furthermore, the proposed method has been implemented on the historical student enrollments data of University of Alabama and obtains the forecasted values which have been compared with the existing methods to show its superiority. The suitability of the proposed model has also been examined to forecast the movement of share market price of State Bank of India (SBI) at Bombay Stock Exchange (BSE). The results of the comparison of MSE and MAPE indicate that the proposed method produces more accurate forecasting results.
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Ayağ, Zeki. "A comparison study of fuzzy-based multiple-criteria decision-making methods to evaluating green concept alternatives in a new product development environment." International Journal of Intelligent Computing and Cybernetics 14, no. 3 (2021): 412–38. http://dx.doi.org/10.1108/ijicc-03-2021-0040.
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PurposeIn this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.Design/methodology/approachThe demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.FindingsThe incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.Research limitations/implicationsThe designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.Practical implicationsThe case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.Social implicationsInclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.Originality/valueThe objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.
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Zhang, Zhen, and Pengfei Su. "Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method." Mathematical Problems in Engineering 2022 (April 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/7445250.
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The English classroom teaching effect evaluation is looked as the multiattribute group decision-making (MAGDM). Thus, a useful MAGDM algorithm is needed to cope with it. Depending on the classical GRA process and interval-valued IFSs (IVIFSs), this study builds the IVIF-GRA process to assess the English classroom teaching effect. First of all, the concepts of IVIFSs are reviewed. In addition, the weights of criteria are derived through the CRITIC method. Afterwards, the GRA model is extended to IVIFSs to get the final result of the alternative. Therefore, all alternatives could be ranked and the optimal one with English classroom teaching effect can be identified. At last, a given numerical example and some given comparative studies are obtained. The analysis results show that the defined algorithms are effective for solving the English classroom teaching effect evaluation.
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Ran, Rong, and Bang-Jun Wang. "Combining grey relational analysis and TOPSIS concepts for evaluating the technical innovation capability of high technology enterprises with fuzzy information." Journal of Intelligent & Fuzzy Systems 29, no. 4 (2015): 1301–9. http://dx.doi.org/10.3233/ifs-141380.
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Sakai, Hiroshi, and Masahiro Inuiguchi. "Special Issue on Rough Sets and Granular Computing." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 5 (2006): 605. http://dx.doi.org/10.20965/jaciii.2006.p0605.
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Rough sets and granular computing, known as new methodologies for computing technology, are now attracting great interest of researchers. This special issue presents 12 articles, and most of them were presented at the second Japanese workshop on Rough Sets held at Kyushu Institute of Technology in Tobata, Kitakyushu, Japan, on August 17-18, 2005. The first article studies the relation between rough set theory and formal concept analysis. These two frameworks are analyzed and connected by using the method of morphism. The second article introduces object-oriented paradigm into rough set theory, and object-oriented rough set models are proposed. Theoretical aspects of these new models are also examined. The third article considers relations between generalized rough sets, topologies and modal logics, and some topological properties of rough sets induced by equivalence relations are presented. The fourth article focuses on a family of polymodal systems, and theoretical aspects of these systems, like the completeness, are investigated. By means of combining polymodal logic concept and rough set theory, a new framework named multi-rough sets is established. The fifth article focuses on the information incompleteness in fuzzy relational models, and a generalized possibility-based fuzzy relational model is proposed. The sixth article presents a developed software EVALPSN (Extended Vector Annotated Logic Program with Strong Negation) and the application of this software to pipeline valve control. The seventh article presents the properties of attribute reduction in variable precision rough set models. Ten kinds of meaningful reducts are newly proposed, and hierarchical relations in these reducts are examined. The eighth article proposes attribute-value reduction for Kansei analysis using information granulation, and illustrative results for some databases in UCI Machine Learning Repository are presented. The ninth article investigates cluster analysis for data with errors tolerance. Two new clustering algorithms, which are based on the entropy regularized fuzzy c-means, are proposed. The tenth article applies binary decision trees to handwritten Japanese Kanji recognition. The consideration to the experimental results of real Kanji data is also presented. The eleventh article applies a rough sets based method to analysing the character of the screen-design in every web site. The obtained character gives us good knowledge to generate a new web site. The last article focuses on rule generation in non-deterministic information systems. For generating minimal certain rules, discernibility functions are introduced. A new algorithm is also proposed for handling every discernibility function. Finally, we would like to acknowledge all the authors for their efforts and contributions. We are very grateful to reviewers for their thorough and on-time reviews, too. We are also grateful to Prof. Toshio Fukuda and Prof. Kaoru Hirota, Editors-in-Chief of JACIII, for inviting us to serve as Guest Editors of this Journal, and to Mr. Uchino and Mr. Ohmori of Fuji Technology Press for their kind assistance in publication of this special issue.
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Wang, Tianxiong, and Liu Yang. "Combining GRA with a Fuzzy QFD Model for the New Product Design and Development of Wickerwork Lamps." Sustainability 15, no. 5 (2023): 4208. http://dx.doi.org/10.3390/su15054208.
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With the popularization of the concept of sustainability in traditional wickerwork, wickerwork lamps have become the most popular production. When customers purchase wickerwork lamp products, the Kansei consensus has become a key factor influencing the communication between manufacturers and customers. Therefore, the purpose of this paper is to explore the product design solutions for wickerwork lamps that meet the emotional satisfaction of users. Firstly, a three-level evaluation grid diagram driven by user attractiveness through Miryoku Engineering is established. Secondly, this paper uses grey relational analysis (GRA) to extract the priority order and its weight values in the perceptual vocabulary to identify the key user needs in product design. In order to effectively deal with the uncertain product evaluation information, the fuzzy quality function deployment (QFD) is used to construct the “emotional demand-design parameter” transformation model and derive the optimal design parameters in the mapping process, thus effectively reducing the ambiguity and uncertainty in the demand transformation process. Based on the experimental results, it is found that the best combination of Texture light transmittance, Simple wickerwork material, Wickerwork primary colours, Cascaded type and Pastoral style could be preferred by customers, thus this proposed method can effectively reduce the ambiguity and uncertainty in the design process. The results of study enable designers to accurately grasp customers’ perceptions of wickerwork lamp products and obtain the best design parameters for wickerwork lamp products.
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Beghriche, Abdesselem, and Azeddine Bilami. "A fuzzy trust-based routing model for mitigating the misbehaving nodes in mobile ad hoc networks." International Journal of Intelligent Computing and Cybernetics 11, no. 2 (2018): 309–40. http://dx.doi.org/10.1108/ijicc-04-2017-0038.
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PurposeSecurity is one of the major challenges in the design and implementation of protocols for mobile ad hoc networks (MANETs). In such systems, the cooperation between nodes is one of the important principles being followed in the current research works to formulate various security protocols. Many existing works assume that mobile nodes will follow prescribed protocols without deviation. However, this is not always the case, because these networks are subjected to a variety of malicious attacks. Since there are various models of attack, trust routing scheme can guarantee security and trust of the network. The purpose of this paper is to propose a novel trusted routing model for mitigating attacks in MANETs.Design/methodology/approachThe proposed model incorporates the concept of trust into the MANETs and applies grey relational analysis theory combined with fuzzy sets to calculate a node’s trust level based on observations from neighbour nodes’ trust level, these trust levels are then used in the routing decision-making process.FindingsIn order to prove the applicability of the proposed solution, extensive experiments were conducted to evaluate the efficiency of the proposed model, aiming at improving the network interaction quality, malicious node mitigation and enhancements of the system’s security.Originality/valueThe proposed solution in this paper is a new approach combining the fundamental basics of fuzzy sets with the grey theory, where establishment of trust relationships among participating nodes is critical in order to enable collaborative optimisation of system metrics. Experimental results indicate that the proposed method is useful for reducing the effects of malicious nodes and for the enhancements of system’s security.
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Wu, Kuo-Jui, Ching-Jong Liao, MingLang Tseng, and Kevin Kuan-Shun Chiu. "Multi-attribute approach to sustainable supply chain management under uncertainty." Industrial Management & Data Systems 116, no. 4 (2016): 777–800. http://dx.doi.org/10.1108/imds-08-2015-0327.
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Purpose – The purpose of this paper is to enhance the understanding of sustainable supply chain management (SSCM) and provide a comprehensive and quantitative method to assess performance. Design/methodology/approach – The study applied interval-valued triangular fuzzy numbers associated with grey relational analysis to improve the insufficient information and overcome the incomplete system under uncertainty. Findings – The findings support the argument that the triple bottom line is insufficient to cover the entire concept of SSCM; in particular, the aspects of operations, stakeholders and resilience have not been addressed in previous studies. Research limitations/implications – The results reveal that the triple bottom line concept is insufficient to illustrate the principles of SSCM and to provide an extensive basis for theory development. The aspects and criteria considered in the study only relate to the studied company and may need to be reviewed when applied to other industries. Practical implications – The methodology and findings of the study demonstrate the core applications of criteria ranking and identify priority areas that utilize less investment but that may maintain the studied company’s current performance. Suggestions for the prioritization of criteria to enhance SSCM performance are provided. Originality/value – The present study provides three valuable contributions. First, it adopts collaboration theory to furnish a theoretical foundation for SSCM. Second, the proposed hybrid method is able to overcome uncertainty and subsequently evaluate SSCM while utilizing incomplete and imprecise information. Third, the evaluation provides significant results for consideration in decision making by the studied company.
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Asees Awan, Muhammad, and Yousaf Ali. "Sustainable modeling in reverse logistics strategies using fuzzy MCDM." Management of Environmental Quality: An International Journal 30, no. 5 (2019): 1132–51. http://dx.doi.org/10.1108/meq-01-2019-0024.
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Purpose Globalization in supply chain networks is urging manufacturing companies for the production of sustainable products with re-engineering technologies that offer competitive advantage in current market. However, the increasing sustainable illumes are influencing reverse logistics (RL) systems to analyze their impacts on economy, environment and society. Recently, China’s $62bn investment under the egis of China Pakistan Economic Corridor (CPEC), which comprises a number of infrastructure and energy projects is developing Pakistan as a part of “One Belt One Road” initiative. Accordingly, a substantial number of economical, ecological and social exercises will occur in closest future. The purpose of this paper is to investigate the impact of sustainable practices, i.e., environmental, economic and social sustainability on RL recovery options. Design/methodology/approach Sustainable concepts including environmental, economic and social and RL recovery options are extracted through extensive literature review. A number of researchers used a variety of methodologies for achieving their research objectives. However, the authors will be using a combination of VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) and grey relational analysis (GRA) technique under fuzzy environment in the case of CPEC. Findings Results show that waste management, impact on bio-diversity and economic growth are the most significant factors in designing sustainable RL recovery options. Moreover, remanufacture and reuse rank top among RL recovery options due their significant economic and environmental effects, whereas recycle and resell position last due to their high cost and cutting edge modern technologies. Practical implications Finally based on this model, it is possible for authorities to design a sustainable RL strategy for efficient operations in case of CPEC projects and other developing countries as well. Originality/value Negligible work has been done regarding sustainable modeling in RL strategies using a combination of VIKOR and GRA techniques subjected to fuzzy environment in the case of CPEC from perspective of developing country, i.e., Pakistan.
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Jafarzadeh Ghoushchi, Saeid, Mohd Nizam Ab Rahman, Diba Raeisi, Elnaz Osgooei, and Majid Jafarzadeh Ghoushji. "Integrated Decision-Making Approach Based on SWARA and GRA Methods for the Prioritization of Failures in Solar Panel Systems under Z-Information." Symmetry 12, no. 2 (2020): 310. http://dx.doi.org/10.3390/sym12020310.
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Encountering a problem or error in the final stages of providing products or services increases costs and delays scheduling. The key task is to ensure quality and reliability in the early stages of the production process and prevent errors from occurring from the beginning. Failure mode and effect analysis (FMEA) is one of the tools for identifying potential problems and their impact on products and services. The conventional FMEA technique has been criticized extensively due to its disadvantages. In this study, the concepts of uncertainty and reliability are considered simultaneously. The processes of weighting risk factors, prioritizing failures by using the stepwise weight assessment ratio analysis (SWARA)–gray relational analysis (GRA) integrated method based on Ζ-number theory and complete prioritization of failures are implemented. Crucial management indices, such as cost and time, are considered in addition to severity, occurrence and detection factors along with assigning symmetric form of the weights to them. This, in turn, increases the interpretability of results and reduces the decision-maker’s subjectivity in risk prioritization. The developed model is implemented on solar panel data with 19 failure modes determined by the FMEA team. Results show that the proposed approach provides a more complete and realistic prioritization of failures than conventional FMEA and fuzzy GRA methods do.
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Tseng, Ming-Lang, Tat-Dat Bui, Ming K. Lim, Feng Ming Tsai, and Raymond R. Tan. "Comparing world regional sustainable supply chain finance using big data analytics: a bibliometric analysis." Industrial Management & Data Systems 121, no. 3 (2021): 657–700. http://dx.doi.org/10.1108/imds-09-2020-0521.
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PurposeSustainable supply chain finance (SSCF) is a fascinated consideration for both academics and practitioners because the indicators are still underdeveloped in achieving SSCF. This study proposes a bibliometric data-driven analysis from the literature to illustrate a clear overall concept of SSCF that reveals hidden indicators for further improvement.Design/methodology/approachA hybrid quantitative and qualitative approach combining data-driven analysis, fuzzy Delphi method (FDM), entropy weight method (EWM) and fuzzy decision-making trial and evaluation laboratory (FDEMATEL) is employed to address the uncertainty in the context.FindingsThe results show that blockchain, cash flow shortage, reverse factoring, risk assessment and triple bottom line (TBL) play significant roles in SSCF. A comparison of the challenges and gaps among different geographic regions is provided in both advanced local perspective and a global state-of-the-art assessment. There are 35 countries/territories being categorized into five geographic regions. Of the five regions, two, Latin America and the Caribbean and Africa, show the needs for more improvement, exclusively in collaboration strategies and financial crisis. Exogenous impacts of wars, natural disasters and disease epidemics are implied as inevitable attributes for enhancing the sustainability.Originality/valueThis study contributes to (1) boundary SSCF foundations by data driven, (2) identifying the critical SSCF indicators and providing the knowledge gaps and directions as references for further examination and (3) addressing the gaps and challenges in different geographic regions to provide advanced assessment from local viewpoint and to diagnose the comprehensive global state of the art of SSCF.
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Lin, Chinho, Shu-Fang Ting, Leslie Lee, and Sheng-Tun Lin. "Firm capability assessment via the BSC and DEA." Industrial Management & Data Systems 121, no. 3 (2021): 567–93. http://dx.doi.org/10.1108/imds-07-2020-0405.
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PurposeThis study proposes an objective assessment model to evaluate the performance of internal and external capabilities of firms. It facilitates firms to invest appropriate resources to cultivate the organizational capability necessary to meet the requirements of the performance indicators.Design/methodology/approachThis study integrates the concepts of resource-based theory, the organizational capability concept, and conduct a performance analysis to the four perspectives of the BSC by implementing the fuzzy set theory and data employment analysis.FindingsThe findings show that the appropriate strategies help allocate available resources and capabilities during the different product life cycle, which provides practical guidelines for firms to achieve sustaining competitive advantage.Research limitations/implicationsThe selected factors were focused on four resources and capabilities rather than all possible factors.Originality/valueAn objective assessment model was created based on internal and external competitive performance efficiency in this research field. This model facilitates the ability of the top management to make decisions for resource allocation that will enhance firm's performance.
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Lan, Shulin, Hao Zhang, Ray Y. Zhong, and G. Q. Huang. "A customer satisfaction evaluation model for logistics services using fuzzy analytic hierarchy process." Industrial Management & Data Systems 116, no. 5 (2016): 1024–42. http://dx.doi.org/10.1108/imds-09-2015-0389.
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Purpose – As the modern manufacturing twining seamlessly with logistics operations for value adding services, logistics service is becoming more and more significant. Under this research background, the purpose of this paper is to introduce an innovative evaluation model for customer satisfaction using fuzzy analytic hierarchy process (FAHP). Design/methodology/approach – This model uses triangular fuzzy concept to determine the weight of each index so that subjective or objective weighting is addressed. A case study from two large express companies in China is used to demonstrate the feasibility and practicality of the proposed model for examining customer satisfaction. Findings – One of the key findings is that Company B has higher customer satisfaction than Company A due to its quick response and flexible logistics strategy. This paper has several contributions. First, A FAHP-based customer satisfaction evaluation model is proposed for the logistics service. Second, the triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method. Third, a case study demonstrates the implementation of the model. Research limitations/implications – First, this paper considers the fuzzy AHP for the customer satisfaction evaluation. Comparing with other multi-criteria decision-making methods like data envelopment analysis, evidential reasoning approach, and multi-attribute value theory will be carried out in the near future. Second, the manufacturing modes like make-to-order, make-to-stock, and mass-customized production may have different logistics support so that the final products may reach the final targets quickly. How to evaluate various mode-based logistics and their customer satisfactions have great significance. Finally, Big Data-enabled customer satisfaction evaluation approaches may be a possible solution. Practical implications – Based on the data from questionnaire, it is found that, in practical applications, manufacturing enterprises should amend the index system according to the specific business scope and the production characteristics. Manufacturing enterprises need to collect large amounts of data through market research and conduct the measurement on the related coefficient between the measurement indicators and customer satisfaction degree. After that, they can make sorting and filtering on the measurement index according to the measurement results. Social implications – Customer satisfaction is very important to manufacturing and logistics enterprises due to its time constraints. The physical products with services like logistics are paid close attention to by the final customers. Originality/value – The contribution of this paper is as follows: a FAHP-based customer satisfaction evaluation model is proposed for the logistics service; triangular fuzzy concept is introduced to determine the weight of each index so as to addresses the limitation of subjective or objective weighting method; a case study was used to demonstrate the implementation of the model. One of the key findings is that Company B has higher customer satisfaction than Company B due to its quick response and flexible logistics strategy.
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Wang, Tianxiong. "A Novel Approach of Integrating Natural Language Processing Techniques with Fuzzy TOPSIS for Product Evaluation." Symmetry 14, no. 1 (2022): 120. http://dx.doi.org/10.3390/sym14010120.
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Product designers need to fully understand consumers’ emotional preferences and responses for product forms to improve products. However, users and designers have different understandings and concepts in the product evaluation process, which will lead to cognitive asymmetry in the product design and evaluating process. This phenomenon prevents designers to grasp users’ needs, increasing the risk of product development failure. To this end, this paper proposes a product evaluation method that combines natural language processing techniques and fuzzy multi-criteria decision-making into a new integrated way to reduce the cognitive difference between users and designers, so as to solve the problem of cognitive asymmetry. This was done firstly by obtaining the review data of products from users on the Internet, based on a web crawler, and then constructing word vectors based on natural language processing techniques to realize the parametric expression of the Kansei image. Secondly, by using a statistical method to extract the product scheme that meets the preferences of users and designers, and then quantifying the relationship between the product form and Kansei image based on a grey relational analysis (GRA). Finally, by calculating the indicator weight based on the Entropy method and using the fuzzy TOPSIS method to explore the prioritization of the product design alternatives in view of the Kansei needs of users. Taking the smart capsule coffee machine as an example, the feasibility and effectiveness of this method are verified. In particular, the method proposed in this research can not only enable different cognitive subjects to achieve cognitive symmetry, but also filter out product forms that meet the cognitive needs of users. Moreover, this study provides a theoretical basis and practical significance for reducing the cognitive differences between cognitive subjects in the whole process of product design, and provides a systematic framework for the industry to effectively connect customer needs and product design decisions. At the same time, this study has introduced a new method for Kansei engineering.
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Rouane-Hacene, Mohamed, Marianne Huchard, Amedeo Napoli, and Petko Valtchev. "Relational concept analysis: mining concept lattices from multi-relational data." Annals of Mathematics and Artificial Intelligence 67, no. 1 (2013): 81–108. http://dx.doi.org/10.1007/s10472-012-9329-3.
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Štěpnička, Martin, Nhung Cao, Michal Burda, Aleš Dolný, and Stanislav Ožana. "The concept of unavoidable features in fuzzy relational compositions." Knowledge-Based Systems 196 (May 2020): 105785. http://dx.doi.org/10.1016/j.knosys.2020.105785.
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Tayal, Devendra K., and P. C. Saxena. "Multivalued Dependencies in Fuzzy Multivalued Relational Databases Using Fuzzy Functions." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, no. 04 (2015): 589–626. http://dx.doi.org/10.1142/s0218488515500269.
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In this paper we discuss an important integrity constraint called multivalued dependency (mvd), which occurs as a result of the first normal form, in the framework of a newly proposed model called fuzzy multivalued relational data model. The fuzzy multivalued relational data model proposed in this paper accommodates a wider class of ambiguities by representing the domain of attributes as a “set of fuzzy subsets”. We show that our model is able to represent multiple types of impreciseness occurring in the real world. To compute the equality of two fuzzy sets/values (which occur as tuple-values), we use the concept of fuzzy functions. So the main objective of this paper is to extend the mvds in context of fuzzy multivalued relational model so that a wider class of impreciseness can be captured. Since the mvds may not exist in isolation, a complete axiomatization for a set of fuzzy functional dependencies (ffds) and mvds in fuzzy multivalued relational schema is provided and the role of fmvds in obtaining the lossless join decomposition is discussed. We also provide a set of sound Inference Rules for the fmvds and derive the conditions for these Inference Rules to be complete. We also derive the conditions for obtaining the lossless join decomposition of a fuzzy multivalued relational schema in the presence of the fmvds. Finally we extend the ABU's Algorithm to find the lossless join decomposition in context of fuzzy multivalued relational databases. We apply all of the concepts of fmvds developed by us to a real world application of “Technical Institute” and demonstrate that how the concepts fit well to capture the multiple types of impreciseness.
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GOMES, M. M. "A concept analysis of relational aggression." Journal of Psychiatric and Mental Health Nursing 14, no. 5 (2007): 510–15. http://dx.doi.org/10.1111/j.1365-2850.2007.01120.x.
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Yager, Ronald R. "Concept Representation and Database Structures in Fuzzy Social Relational Networks." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 40, no. 2 (2010): 413–19. http://dx.doi.org/10.1109/tsmca.2009.2036591.
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Wang, Shyue-Liang, Tzung-Pei Hong, and Wen-Yang Lin. "Answering Null Queries by Analogical Reasoning on Similarity-based Fuzzy Relational Databases." Journal of Advanced Computational Intelligence and Intelligent Informatics 5, no. 3 (2001): 163–71. http://dx.doi.org/10.20965/jaciii.2001.p0163.
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We present here a method of using analogical reasoning to infer approximate answers for null queries on similarity-based fuzzy relational databases. Null queries are queries that elicit a null answer from a database. Analogical reasoning assumes that if two situations are known to be similar in some respects, it is likely that they will be similar in others. Application of analogical reasoning to infer approximate answers for null queries using fuzzy functional dependency and fuzzy equality relation on possibility-based fuzzy relational database has been studied. However, the problem of inferring approximate answers has not been fully explored on the similarity-based fuzzy relational data model. In this work, we introduce the concept of approximate dependency and define a similarity measure on the similaritybased fuzzy model, as extensions to the fuzzy functional dependency and fuzzy equality relation respectively. Under the framework of reasoning by analogy, our method provides a flexible query answering mechanism for null queries on the similarity-based fuzzy relational data model.
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Bartl, Eduard, and Jan Konecny. "Rough Fuzzy Concept Analysis." Fundamenta Informaticae 156, no. 2 (2017): 141–68. http://dx.doi.org/10.3233/fi-2017-1601.
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Anthvanet, L. Jeromia, A. Rajkumar, and D. Nagarajan. "A Study on Plithogenic Fuzzy Relational Mapping and Its Application in Python Program." International Journal of Neutrosophic Science 19, no. 02 (2022): 42–56. http://dx.doi.org/10.54216/ijns.190204.
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In this research paper, we explore the notion of Plithogenic Fuzzy Relational Mapping (PFRM) and its applications. Plithogenic Fuzzy Relational Mapping concept is utilized as a logical procedure with a defined contradiction degree to evaluate multiple attributes. A Plithogenic fuzzy relational matrix is used as the adjacency matrix. Using Plithogenic fuzzy union and intersection operators, the resultant vector is calculated. The degree of contradiction for each attribute value with the dominating attribute gives a way to better accurate results. A case study has been taken and we have implemented the newly proposed idea. Python Program has been written using the algorithm proposed and we have obtained the result as well.
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Azzeh, Mohammad, Daniel Neagu, and Peter I. Cowling. "Fuzzy grey relational analysis for software effort estimation." Empirical Software Engineering 15, no. 1 (2009): 60–90. http://dx.doi.org/10.1007/s10664-009-9113-0.
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Liu, Julie Yu-Chih. "Lossless Join Decomposition for Extended Possibility-Based Fuzzy Relational Databases." Journal of Applied Mathematics 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/842680.
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Functional dependency is the basis of database normalization. Various types of fuzzy functional dependencies have been proposed for fuzzy relational database and applied to the process of database normalization. However, the problem of achieving lossless join decomposition occurs when employing the fuzzy functional dependencies to database normalization in an extended possibility-based fuzzy data models. To resolve the problem, this study defined fuzzy functional dependency based on a notion of approximate equality for extended possibility-based fuzzy relational databases. Examples show that the notion is more applicable than other similarity concept to the research related to the extended possibility-based data model. We provide a decomposition method of using the proposed fuzzy functional dependency for database normalization and prove the lossless join property of the decomposition method.
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GARRIDO, CARMEN, NICOLÁS MARÍN, and OLGA PONS. "FUZZY INTERVALS TO REPRESENT FUZZY VALID TIME IN A TEMPORAL RELATIONAL DATABASE." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17, supp01 (2009): 173–92. http://dx.doi.org/10.1142/s021848850900608x.
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Temporal databases offer a common framework to those database applications that need to store or handle different types of temporal data from a variety of sources. They allow the concept of time to be handled from the point of view of meaning, representation, and manipulation. Although at first sight the incorporation of time into a database might appear to be a direct and simple task, it is, however, quite complex: not only must new structures and specific operators be included, but the semantics of conventional DML sentences (insert, update, or delete) and queries must be appropriately changed. In addition, temporal information is not always as precise as desired since it might be affected by imprecision due to the use of natural language or to the nature of the information source. In this paper, we deal with the problem of the update (and, implicitly, insert and delete) and query operations when time is expressed by means of a fuzzy interval of dates.
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Sahu, Anoop Kumar, Atul Kumar Sahu, and Nitin Kumar Sahu. "Appraisements of material handling system in context of fiscal and environment extent." International Journal of Logistics Management 28, no. 1 (2017): 2–28. http://dx.doi.org/10.1108/ijlm-09-2015-0163.
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Purpose In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS hierarchical module consists of ecological cum fiscal criteria. Moreover, similar literature review assisted the authors to resolve and eventually construct the effectual and robust approach. The purpose of this paper is to facilitate the managers for benchmarking the MHS alternatives operating under similar module via robust decision support system (DSS). Design/methodology/approach In present research, the proposed module dealt with ecological (subjective) and fiscal (objective) criteria, where subjective criteria associated with incompleteness, vagueness, imprecision, as well as inconsistency, solicited the discrete information in terms of Grey set via linguistic scale from experts panel. The objective information (capital) has been assigned by expert’s panel in terms of Grey set. To robustly evaluate and select the admirable MHS, three approaches named: degree of possibility, technique for order preference similar to ideal solution as well as Grey relational analysis fruitfully applied to connect and unite discrete information. Findings The performance evaluation of MHSs has been carried out under concert of individual fiscal criteria excluding ecological criteria in past researches. Moreover the previous developed DSS tackled sole approach under individual fiscal criteria. The authors found the broad applications of fuzzy sets except Grey set theory in the same context for measuring the performance of MHS alternatives. Aforesaid research gaps have been transformed into research objectives by incorporating the module for both fiscal cum ecological criteria. This research embraces a robust DSS, which has been explored to select the admirable MHS alternative. Originality/value An empirical case study has been carried out in order to demonstrate the legitimacy of holistic Grey-MCDM method, implemented over multi criteria MHS hierarchical module. Proposed DSS seems to be the best for organisations, which believe to appraise and select the MHS including fiscal as well as ecological criteria excluding individual fiscal criteria. Moreover, subjective cum objective or individual subjective or objective criteria can be extended with respect to varieties of MHSs.
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Vuong, Le Tien. "On the application of fuzzy set theory in relational database." Journal of Computer Science and Cybernetics 1, no. 4 (2015): 10–15. http://dx.doi.org/10.15625/1813-9663/1/4/6699.
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In this paper, we introduced a model of retrieval system based on the theory of fuzzy sets in which we constructed a suitable storage structure with incomplete inverted files (they contain even some incomplete inverted files for a collection of fuzzy data of database). In this concept, we introduced a method for fuzzy query processing in the system and shown some retrieval strategies. The general response system was also defined and the ability of these strategies was investigated.
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Pakkar, Mohammad Sadegh. "An integrated approach to grey relational analysis, analytic hierarchy process and data envelopment analysis." Journal of Centrum Cathedra 9, no. 1 (2016): 71–86. http://dx.doi.org/10.1108/jcc-08-2016-0005.
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Purpose This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers. Design/methodology/approach This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative. Findings The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach. Originality/value This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.
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Myszkorowski, Krzysztof. "FUZZY RECURSIVE RELATIONSHIPS IN RELATIONAL DATABASES." Information System in Management 7, no. 1 (2018): 35–46. http://dx.doi.org/10.22630/isim.2018.7.1.4.
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Recursive relationships are used for modelling problems coming from the real life, such as, for example, a relationship describing formal dependencies between employees of an enterprise, where creation of work groups and teams requires analysis of many elements. In conventional database systems, the precision of data is assumed. If our knowledge of the fragment of reality to be modelled is imperfect one should apply tools for describing uncertain or imprecise information. One of them is the fuzzy set theory. The paper deals with recursive relationships in fuzzy databases. The analysis is performed with the use of the theory of interval-valued fuzzy sets. A definition of a fuzzy interval recursive relationship has been presented. The paper defines different connections of entities which participate in such relationships. Op-erations of the extended relational algebra are also discussed.
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Guan, Xin, Guidong Sun, Xiao Yi, and Jing Zhao. "Grey Relational Analysis for Hesitant Fuzzy Sets and Its Applications to Multiattribute Decision-Making." Mathematical Problems in Engineering 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/7436054.
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Due to the superiority in expressing the uncertain and vague information, the hesitant fuzzy set (HFS) is regarded as an important tool to deal with multiattribute decision-making (MADM) problems. Quantitative and qualitative fuzzy measures have been proposed to solve such problems from different points. However, most of the existing information measures for HFSs are related to such fuzzy measures as distance, similarity, entropy, and correlation coefficients. The grey relational analysis is omitted. Besides, the existing grey relational analysis for HFSs only considers the range or distance between HFSs data which is only a partial measure of the HFSs. Therefore, in this paper, we improve the grey relational analysis for HFSs and explore a novel slope grey relational degree by considering another factor of HFSs data: the slope. Further, we combine both the distance and slope factors of HFSs data to construct a synthetic grey relational degree that describes the closeness and variation tendency of HFSs simultaneously, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs MADM problems. Finally, combining with two practical MADM examples about energy policy selection and multisensor target recognition, we obtain the most desirable decision results. Compared with the previous methods, the validity, comprehensiveness, and discrimination of the proposed synthetic grey relational degree for HFSs are demonstrated in detail.
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Guesmi, Soumaya, Chiraz Trabelsi, and Chiraz Latiri. "Community detection in multi-relational social networks based on relational concept analysis." Procedia Computer Science 159 (2019): 291–300. http://dx.doi.org/10.1016/j.procs.2019.09.184.
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Li, Lan Yun, Zhuan Zhao Yang, and Zhi He. "Research on Fault Recognition for Centrifugal Compressor Based on Fuzzy Gray Relational Grade." Applied Mechanics and Materials 26-28 (June 2010): 71–76. http://dx.doi.org/10.4028/www.scientific.net/amm.26-28.71.
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In practical centrifugal compressor fault diagnosis, it is very difficult to improve the fault recognition rate, especially when the sample sizes are small. To solve this problem, a new fault recognition method based on fuzzy gray relational grade was proposed. Firstly, according to fuzzy set theory, the fuzzy relation coefficient (FRC), fuzzy relation degree (FRD) and fuzzy relative weights (FRW) of all fault features were calculated. Secondly, the gray system theory was used to obtain the gray relational coefficients (GRC). Thirdly, by combining FRW and GRC, two fuzzy gray relation grades (FGRG) were presented, which is the Hamming distance-based fuzzy gray relation grade (HD-FGRG) and the Euclidean distance-based fuzzy gray relation grade (ED-FGRG), respectively. Finally, the fault recognition results were obtained by using the max membership degree principle. The centrifugal compressor fault diagnosis results show that the ED-FGRG method is more effective and accurate than traditional gray relational analysis (T-GRA) method, the weighted gray relational analysis (W-GRA) method, and the entropy weight-based gray relational analysis (EW-GRA) method and the HD-FGRG method.
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Xu, Chen-Wei. "Analysis and feedback/feedforward control of fuzzy relational systems." Fuzzy Sets and Systems 35, no. 1 (1990): 105–13. http://dx.doi.org/10.1016/0165-0114(90)90023-y.
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Wang, C. C. L., S. F. Chen, and M. M. F. Yuen. "Fuzzy Part Family Formation Based on Grey Relational Analysis." International Journal of Advanced Manufacturing Technology 18, no. 2 (2001): 128–32. http://dx.doi.org/10.1007/s001700170083.
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