Search results for "Fuzzy set operations"

showing 10 items of 41 documents

Introducing a Fuzzy-Pattern Operator in Fuzzy Time Series

2017

In this paper we introduce a fuzzy pattern operator and propose a new weighting fuzzy time series strategy for generating accurate ex-post forecasts. A decision support system is built for managing the weights of the information provided by the historical data, under a fuzzy time series framework. Our procedure analyzes the historical performance of the time series using different experiments, and it classifies the characteristics of the series through a fuzzy operator, providing a trapezoidal fuzzy number as one-step ahead forecast. We also present some numerical results related to the predictive performance of our procedure with time series of financial data sets.

0209 industrial biotechnologyFuzzy classificationSeries (mathematics)Computer science02 engineering and technologycomputer.software_genreDefuzzificationFuzzy logicWeighting020901 industrial engineering & automationFuzzy mathematics0202 electrical engineering electronic engineering information engineeringFuzzy numberFuzzy set operations020201 artificial intelligence & image processingData miningcomputer
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Optimal control of discrete-time interval type-2 fuzzy-model-based systems with D-stability constraint and control saturation

2016

This paper investigates the optimal control problem for discrete-time interval type-2 (IT2) fuzzy systems with pole constraints. An IT2 fuzzy controller is characterized by two predefined functions, and the membership functions and the premise rules of the IT2 fuzzy controller can be chosen freely. The pole assignment is considered, which is constrained in a presented disk region. Based on Lyapunov stability theory, sufficient conditions of asymptotic stability with an H ∞ performance are obtained for the discrete-time IT2 fuzzy model based (FMB) system. Based on the criterion, the desired IT2 state-feedback controller is designed to guarantee that the closed-loop system is asymptotically s…

0209 industrial biotechnologyMathematical optimizationAdaptive neuro fuzzy inference system02 engineering and technologyFuzzy control systemOptimal controlDefuzzificationFuzzy logic020901 industrial engineering & automationControl and Systems EngineeringControl theorySignal Processing0202 electrical engineering electronic engineering information engineeringFuzzy set operationsFuzzy number020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionElectrical and Electronic EngineeringSoftwareMathematicsSignal Processing
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Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series

2015

Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algor…

Adaptive neuro fuzzy inference systemComputer scienceCognitive NeuroscienceFuzzy setcomputer.software_genreStock market indexDefuzzificationFuzzy logicComputer Science ApplicationsArtificial IntelligenceFuzzy set operationsRough setData miningFutures contractcomputerNeurocomputing
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Upper and lower generalized factoraggregations based on fuzzy equivalence relation

2014

We develop the concept of a general factoraggre-gation operator introduced by the authors on the basis of an equivalence relation and applied in two recent papers for analysis of bilevel linear programming solving parameters. In the paper this concept is generalized by using a fuzzy equivalence relation instead of the crisp one. By using a left-continuous t-norm and its residuum we define and investigate two modifications of such generalized construction: upper and lower generalized factoraggregations. These generalized factoraggregations can be used for construction of extensional fuzzy sets.

AlgebraDiscrete mathematicsFuzzy classificationFuzzy setEquivalence relationFuzzy numberGeneralized linear array modelFuzzy set operationsFuzzy subalgebraDefuzzificationMathematics2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
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Fixed points in weak non-Archimedean fuzzy metric spaces

2011

Mihet [Fuzzy $\psi$-contractive mappings in non-Archimedean fuzzy metric spaces, Fuzzy Sets and Systems, 159 (2008) 739-744] proved a theorem which assures the existence of a fixed point for fuzzy $\psi$-contractive mappings in the framework of complete non-Archimedean fuzzy metric spaces. Motivated by this, we introduce a notion of weak non-Archimedean fuzzy metric space and prove that the weak non-Archimedean fuzzy metric induces a Hausdorff topology. We utilize this new notion to obtain some common fixed point results for a pair of generalized contractive type mappings.

Common fixed points Weak non-Archimedean fuzzy metric spaces Fuzzy contractive mappingsDiscrete mathematicsFuzzy classificationMathematics::General MathematicsLogicInjective metric spaceT-normFuzzy subalgebraIntrinsic metricConvex metric spaceComputingMethodologies_PATTERNRECOGNITIONSettore MAT/05 - Analisi MatematicaArtificial IntelligenceFuzzy set operationsFuzzy numberComputingMethodologies_GENERALMathematicsFuzzy Sets and Systems
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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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Upper and lower approximations of general aggregation operators based on fuzzy rough sets

2015

Our paper deals with constructions of upper and lower general aggregation operators which act on fuzzy sets. These constructions are based on fuzzy rough sets and provide two approximations (upper and lower) of the pointwise extension and the t-extension of an ordinary aggregation operator. Considering two lattices of corresponding general aggregation operators we describe two approximate systems with respect to a lattice of fuzzy equivalence relations.

Discrete mathematicsPure mathematicsFuzzy classificationFuzzy mathematicsFuzzy setFuzzy set operationsFuzzy numberRough setFuzzy subalgebraDefuzzificationMathematics2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)
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A Fuzzy Discrete Event Simulator for Fuzzy Production Environment Analysis

1998

Abstract Discrete Event Simulation is a powerful tool to help production managers in planning manufacturing systems. The necessity to rapid react to market conditions is pushing production planners to process requirements and information affected by vagueness. Vagueness is related with event definition, therefore it is not manageable through statistical tools, but more properly by using fuzzy mathematics. Production situations where uncertainty takes body in term of vagueness are referred as Fuzzy Production Environments. Classical Discrete Event simulators are not suitable to deal with fuzzy variables, therefore they cannot be used to model Fuzzy Production Environments. This paper aims to…

EngineeringNeuro-fuzzyEvent (computing)business.industryMechanical EngineeringVaguenessFuzzy control systemFuzzy logicIndustrial and Manufacturing EngineeringFuzzy mathematicsFuzzy set operationsDiscrete event simulationbusinessSimulationCIRP Annals
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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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Fuzzy methods for analysing fuzzy production environment

1998

Abstract Very recently, in production management research literature, the necessity to extend production systems analysis techniques, such as queue theory, Mean Value Analysis (MVA) and discrete simulation, to Fuzzy Production Environments, i.e. to those production situations in which data are vague, has emerged. Fuzzy set theory is a powerful tool to model vagueness and, therefore, fuzzy mathematics can be used to extend classical production system analysis techniques. This paper proposes a methodology based on fuzzy relation algebra to extend classical MVA and discrete event simulation.

Fuzzy classificationFuzzy measure theorybusiness.industryGeneral MathematicsFuzzy setcomputer.software_genreDefuzzificationFuzzy logicIndustrial and Manufacturing EngineeringComputer Science ApplicationsControl and Systems EngineeringFuzzy mathematicsFuzzy set operationsFuzzy numberArtificial intelligenceData miningbusinesscomputerSoftwareMathematicsRobotics and Computer-Integrated Manufacturing
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