Search results for "type-2 fuzzy sets"

showing 10 items of 15 documents

Fuzzy functions: a fuzzy extension of the category SET and some related categories

2000

<p>In research Works where fuzzy sets are used, mostly certain usual functions are taken as morphisms. On the other hand, the aim of this paper is to fuzzify the concept of a function itself. Namely, a certain class of L-relations F : X x Y -> L is distinguished which could be considered as fuzzy functions from an L-valued set (X,Ex) to an L-valued set (Y,Ey). We study basic properties of these functions, consider some properties of the corresponding category of L-valued sets and fuzzy functions as well as briefly describe some categories related to algebra and topology with fuzzy functions in the role of morphisms.</p>

Discrete mathematicsFuzzy classificationL-relationFuzzy topologylcsh:MathematicsFuzzy setlcsh:QA299.6-433Fuzzy subalgebralcsh:AnalysisFuzzy groupType-2 fuzzy sets and systemslcsh:QA1-939DefuzzificationAlgebraFuzzy mathematicsL-fuzzy functionFuzzy numberFuzzy set operationsGeometry and TopologyFuzzy categoryMathematics
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Ranking fuzzy interval numbers in the setting of random sets – further results

1999

Abstract We present some new properties of several fuzzy order relations, defined on the set of fuzzy numbers, from among those introduced in [S. Chanas, M. Delgado, J.L. Verdegay, M.A. Vila, Information Sciences 69 (1993) 201–217]. The main result is proving that four from among the relations considered in [S. Chanas, M. Delgado, J.L. Verdegay, M.A. Vila, Information Sciences 69 (1993) 201–217] are strongly transitive (s-transitive).

Discrete mathematicsTransitive relationInformation Systems and ManagementFuzzy classificationFuzzy setInterval (mathematics)Type-2 fuzzy sets and systemsFuzzy logicComputer Science ApplicationsTheoretical Computer ScienceArtificial IntelligenceControl and Systems EngineeringFuzzy mathematicsFuzzy numberSoftwareMathematicsInformation Sciences
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Representation of knowledge using Fuzzy set theory

1989

Fuzzy classificationComputer sciencebusiness.industryFuzzy setFuzzy mathematicsFuzzy numberFuzzy set operationsArtificial intelligenceFuzzy subalgebrabusinessType-2 fuzzy sets and systemsFuzzy logic
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A fuzzy framework to explain musical tuning in practice

2013

A theoretical tuning system is a set of pitches that can be used to play music. It is a fact that the human ear perceives notes with very close frequencies as if they were the same note. Therefore, in our approach a musical note and its pitch sensation are modeled as L-R fuzzy numbers with a modal interval and a bounded support. We pay particular attention to the 12-tone equal temperament (12-TET) for being the most widely used tuning system and we define the fuzzy 12-TET composed of 12 fuzzy notes. A similarity relation between a fuzzy note and a theoretical note can be defined, and subsequently a similarity class associated to each one of the fuzzy notes in the fuzzy 12-TET arises. Finall…

Fuzzy classificationLogicbusiness.industryMusical tuningMusical noteType-2 fuzzy sets and systemsDefuzzificationFuzzy logicArtificial IntelligenceFuzzy mathematicsFuzzy numberArtificial intelligencebusinessMathematicsFuzzy Sets and Systems
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Fuzzy Classifier Based on Fuzzy Decision Tree

2007

A popular method for making a fuzzy decision tree for classification is Fuzzy ID3 algorithm. We introduce a new approach that uses cumulative information estimations of initial data. Based on these estimations we propose a new greedy version of fuzzy ID3 algorithm to be used to generate understandable fuzzy classification rules. The goal is to find a sequence of rules that causes near minimal classification costs.

Fuzzy classificationNeuro-fuzzybusiness.industryType-2 fuzzy sets and systemscomputer.software_genreMachine learningDefuzzificationComputingMethodologies_PATTERNRECOGNITIONInformation Fuzzy NetworksFuzzy numberFuzzy set operationsFuzzy associative matrixArtificial intelligenceData miningbusinesscomputerMathematicsEUROCON 2007 - The International Conference on "Computer as a Tool"
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Do Uncertainty and Fuzziness Present Themselves (and Behave) in the Same Way in Hard and Human Sciences?

2010

In the present paper the question whether uncertainty and fuzziness present themselves and behave in the same way (or not) in hard and human sciences will be briefly discussed. This problem came out from the attempt to answer the question asked by Lotfi Zadeh on the (apparent) strangeness of a very limited use of fuzzy sets in human sciences.

Hard and soft scienceSettore INF/01 - Informaticabusiness.industryUncertainty fuzziness hard sciences human sciences two cultures use of formal methods in human sciences.Fuzzy setHuman scienceArtificial intelligenceStrangenessType-2 fuzzy sets and systemsbusinessMathematics
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Fuzzy expected utility

1984

Decision making under uncertainty requires not only measures of the uncertainty of situations that we try to recognize , but also an estimate of the imprecision from which they are determined. This imprecision can be the result either of a lack of exactness in the measure of the elements which are necessary to the determination of the states of nature or the purely subjective interpretation of these states. Through a subjective measure of the non-measurable imprecision, the purpose of the fuzzy expected utility, which is investigated, is to translate with a great accuracy the imprecise behaviour of the decision-maker in an uncertain world. Consequently we propose to introduce first the prob…

Mathematical optimizationFuzzy classificationFuzzy measure theoryLogicbusiness.industry[SHS.ECO]Humanities and Social Sciences/Economics and FinanceType-2 fuzzy sets and systemsFuzzy logicDefuzzificationArtificial IntelligenceFuzzy mathematicsFuzzy numberFuzzy set operations[ SHS.ECO ] Humanities and Social Sciences/Economies and financesArtificial intelligencebusiness[SHS.ECO] Humanities and Social Sciences/Economics and FinanceDecision makingFuzzyMathematics
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The fuzzy p-median problem

2004

In many location models, the strong crisp assumptions, like known demands and distances, are not realistic in most cases. The fuzzy p-median problem relaxes this hypothesis giving to the decision maker a necessary degree of freedom to solve real-world problems. It allows a decision maker to improve an optimal covering of a location problem by considering partially feasible solutions in which some demand is left uncovered. Here we revise the main facts and results about this problem emphasising different specific algorithms of resolution. Finally we show that this fuzzy version can be used to analyse the global structure of a given instance of the crisp problem.

Mathematical optimizationFuzzy classificationFuzzy transportationComputer scienceFuzzy setGeneral EngineeringFuzzy set operationsFuzzy numberType-2 fuzzy sets and systemsGeneral Business Management and AccountingDefuzzificationFuzzy logicInternational Journal of Technology, Policy and Management
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Involving fuzzy orders for multi-objective linear programming

2012

This paper presents a solution approach for multi-objective linear programming problem. We propose to involve fuzzy order relations to describe the objective functions where in ”classical” fuzzy approach the membership functions which illustrate how far the concrete point is from the solution of individual problem are studied. Further the global fuzzy order relation is constructed by aggregating the individual fuzzy order relations. Thus the global fuzzy relation contains the information about all objective functions and in the last step we find a maximum in the set of constrains with respect to the global fuzzy order relation. We illustrate this approach by an example.

Mathematical optimizationFuzzy classificationMathematics::General MathematicsFuzzy setmulti-objective linear programmingfuzzy order relationType-2 fuzzy sets and systemsDefuzzificationModeling and SimulationFuzzy mathematicsQA1-939aggregation of fuzzy relationsFuzzy numberFuzzy set operationsMathematicsAnalysisMembership functionMathematicsMathematical Modelling and Analysis
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Controller Design Under Fuzzy Pole-Placement Specifications: An Interval Arithmetic Approach

2006

This paper discusses fuzzy specifications for robust controller design, as a way to define different specification levels for different plants in a family and allow the control of performance degradation. Controller synthesis will be understood as mapping a fuzzy plant onto a desired fuzzy set of closed-loop specifications. In this context, a fuzzy plant is considered as a possibility distribution on a given plant space. In particular, pole placement in linear plants with fuzzy parametric uncertainty is discussed, although the basic idea is general and could be applied to other settings. In the case under consideration, the controller coefficients are the solution of a fuzzy linear system o…

Mathematical optimizationFuzzy classificationNeuro-fuzzyApplied MathematicsFuzzy control systemType-2 fuzzy sets and systemsDefuzzificationFuzzy logicComputational Theory and MathematicsArtificial IntelligenceControl and Systems EngineeringControl theoryFuzzy set operationsFuzzy numberComputingMethodologies_GENERALMathematicsIEEE Transactions on Fuzzy Systems
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