Search results for "fuzzy set"

showing 10 items of 197 documents

General aggregation operators based on a fuzzy equivalence relation in the context of approximate systems

2016

Our paper deals with special constructions of general aggregation operators, which are based on a fuzzy equivalence relation and provide upper and lower approximations of the pointwise extension of an ordinary aggregation operator. We consider properties of these approximations and explore their role in the context of extensional fuzzy sets with respect to the corresponding equivalence relation. We consider also upper and lower approximations of a t-norm extension of an ordinary aggregation operator. Finally, we describe an approximate system, considering the lattice of all general aggregation operators and the lattice of all fuzzy equivalence relations.

Discrete mathematicsPointwiseLogic05 social sciencesFuzzy set050301 educationContext (language use)02 engineering and technologyExtension (predicate logic)Lattice (discrete subgroup)Operator (computer programming)Artificial Intelligence0202 electrical engineering electronic engineering information engineeringEquivalence relationApplied mathematics020201 artificial intelligence & image processing0503 educationOrdered weighted averaging aggregation operatorMathematicsFuzzy Sets and Systems
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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 general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms

1983

All known connectives 'and'/'or' for fuzzy sets or some classes can be introduced as t-norms/t-conorms, where Ling's representation theorem is used as a basic tool, and which is illustrated by various known and new examples (Section 2). Given a strict negation function and one connective, the other can be constructed, so that the corresponding De Morgan law is valid. In case of given Archimedean connectives, there can be constructed negation functions (Section 3). Given a non-strict Archimedean connective, a negation function and the other connective can be constructed, so that in addition to the De Morgan laws, the excluded middle law and the law of non-contradiction are valid, i.e. the ne…

Discrete mathematicsPure mathematicsRepresentation theoremLogicLaw of excluded middleFuzzy setT-normType (model theory)De Morgan's lawssymbols.namesakeNegationArtificial IntelligencesymbolsComplement (set theory)MathematicsFuzzy Sets and Systems
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M-valued Measure of Roughness for Approximation of L-fuzzy Sets and Its Topological Interpretation

2015

We develop a scheme allowing to measure the “quality” of rough approximation of fuzzy sets. This scheme is based on what we call “an approximation quadruple” \((L,M,\varphi ,\psi )\) where L and M are cl-monoids (in particular, \(L=M=[0,1]\)) and \(\psi : L \rightarrow M\) and \(\varphi : M \rightarrow L\) are satisfying certain conditions mappings (in particular, they can be the identity mappings). In the result of realization of this scheme we get measures of upper and lower rough approximation for L-fuzzy subsets of a set equipped with a reflexive transitive M-fuzzy relation R. In case the relation R is also symmetric, these measures coincide and we call their value by the measure of rou…

Discrete mathematicsSet (abstract data type)Identity (mathematics)Transitive relationScheme (mathematics)Fuzzy setTopologyMeasure (mathematics)Realization (systems)Interpretation (model theory)Mathematics
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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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The fall and the fragmentation of national clusters: Cluster evolution in the paper and pulp industry

2012

Abstract A common expectation in evolutionary cluster studies is that national clusters engage in competitive interactions that lead to a continuous stream of changes in global dominance. Our fuzzy-set analysis on the evolution of the paper and pulp industry demonstrates that globalization has dramatically changed this situation. National clusters have largely faded away; the value chain dominance is now held by technology suppliers who are global hubs in majority of identifiable business activities in the focal industry. Our results imply that when industrial decline is accentuated by industrial concentration in some part of the value chain the national clusters may lose their importance.

EcologyGeography Planning and DevelopmentEconomics Econometrics and Finance (miscellaneous)ForestryBusiness activitiesMarket fragmentationGlobalizationEconomyFuzzy set analysisDominance (economics)Cluster (physics)EconomicsPulp industryEconomic geographyValue chainJournal of Forest Economics
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Revisiting bank failure in the United States: a fuzzy-set analysis

2020

Past financial crises have illustrated the importance of recognising the combinations of factors that can cause financial distress in the banking industry. Accordingly, this study uses fuzzy-set qualitative comparative analysis (fsQCA) to identify the combinations of factors that lead to bank failure. The data consist of 30 annual financial ratio series for 156 U.S. banks over a 15-year period (2001–2015). Identifying combinations of conditions that can produce bank failure is crucial to help regulators and bank managers. The fsQCA presented in this paper sheds light on the relationships between combinations of conditions and bank failure, providing a solution comprising two sufficient and …

Economics and Econometricsfood and beveragesFinancial systembank failurebank failure preventionlcsh:Regional economics. Space in economicsBanking industrylcsh:HD72-88lcsh:HT388fuzzy-set qualitative comparative analysis (fsqca)lcsh:Economic growth development planningFuzzy set analysisBank failure; bank failure prevention; bank financial distress; fuzzy-set qualitative comparative analysis (fsQCAFinancial distressBusinessBank failurebank financial distressEkonomska Istraživanja
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Prioritization of students’ needs for education service design and development by embedding AHP and fuzzy set theory: A case study

2015

Student satisfaction represents a strategic factor for many universities towards increasing competition concerning students recruitment. Thus, nowadays many universities take into account typical customer-oriented industry’s approaches for the education service design and development. In such a condition, prioritization of students’ needs represents a crucial step to appropriately adopt these approaches. This paper proposes an effective way to evaluate importance of students’ needs based on the Analytic Hierarchy Process (AHP) method, in which linguistic variables are parameterized by means of triangular fuzzy numbers, to deal with uncertainty, subjectivity and vagueness. Finally, a case st…

Education service qualityStudent’s needs evaluationAHPFuzzy set theorySettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Analysis of operator human errors in hydrogen refuelling stations: Comparison between human rate assessment techniques

2013

Abstract The use of hydrogen as an energy carrier for road transport appears to be an optimal solution for the reduction of greenhouse gas emissions. Nevertheless, the development of this technology depends on the growth and diffusion of production, storage and refuelling infrastructures together with accurate risk analyses to appropriately design the safety and management systems used in these plants. Moreover, to improve safety standards, it is also important to focus attention on the estimation of hazards related to human factors, as this is one of the major causes leading to accidental events, especially in complex industrial technology. The paper reports a case study relevant to operat…

Energy carrierRisk analysisRenewable Energy Sustainability and the EnvironmentComputer scienceFuzzy setFuzzy HEARTEnergy Engineering and Power TechnologySafety standardsCondensed Matter PhysicsHydrogen refuelling stationReliability engineeringRisk analysiFuel TechnologyIndustrial technologyGreenhouse gasManagement systemStorage unitHuman errorHuman error assessment and reduction techniqueCREAMSettore ING-IND/19 - Impianti Nucleari
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A fuzzy logic approach to modeling a vehicle crash test

2013

Published version of an article in the journal: Central European Journal of Engineering. Also available from the publisher at: http://dx.doi.org/10.2478/s13531-012-0032-2 This paper presents an application of fuzzy approach to vehicle crash modeling. A typical vehicle to pole collision is described and kinematics of a car involved in this type of crash event is thoroughly characterized. The basics of fuzzy set theory and modeling principles based on fuzzy logic approach are presented. In particular, exceptional attention is paid to explain the methodology of creation of a fuzzy model of a vehicle collision. Furthermore, the simulation results are presented and compared to the original vehic…

EngineeringEnvironmental Engineeringmedia_common.quotation_subjectFuzzy setAerospace EngineeringFidelityCrashKinematicsFuzzy logicGeneral Materials Sciencevehicle crashElectrical and Electronic EngineeringCivil and Structural Engineeringmedia_commonAdaptive neuro fuzzy inference systemEvent (computing)business.industryMechanical EngineeringVDP::Technology: 500::Mechanical engineering: 570modelingControl engineeringEngineering (General). Civil engineering (General)Collisionfuzzy logicTA1-2040businessOpen Engineering
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