0000000000314341

AUTHOR

Olga Grigorenko

showing 6 related works from this author

Daudzvērtīga sakārtojuma attiecības un monotonie attēlojumi: kategoriju teorijas konstrukcijas un lietojumi agregācijas procesā

2012

Nestrikta sak¯artojuma koncepcija, kas ien¸em centr¯alo vietu m¯usu darb¯a, sp¯el¯e noz¯ım¯ıgu lomu gan teor¯etisk¯as Nestrikt¯as Matem¯atikas jom¯a gan t¯as lietojumos. Disert¯acij¯a m¯es att¯ıst¯am nestrikto sak¯artojumu teoriju divos, iekˇs¯eji saist¯ıtos, virzienos. S¯akum¯a m¯es konstru¯ejam L-v¯ert¯ıgu kategoriju, kuras objekti ir L-E-sak¯artotas kopas. Lai sasniegtu ˇso m¯erk¸i, m¯es konstru¯ejam klasisku kategoriju, kuras objekti ir L-E-sak¯artotas kopas un morfismi ir sak¯artojuma saglab¯ajoˇsas funkcijas. Darb¯a m¯es p¯et¯am konstru¯etas kategorijas pamat¯ıpaˇs¯ıbas. Tad m¯es fazific¯ejam konstru¯eto kategoriju un p¯et¯am ieg¯utas L-v¯ert¯ıgas kategorijas fundament¯alas ¯ıpaˇs¯ıba…

Fizika materiālzinātne matemātika un statistikaMatemātika
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Daudzvērtīgu sakārtojumu attiecības un sakārtotu kopu kategorijas fazifikācija

2006

Maģistra darbs ir veltīts sakārtojuma attiecības fazifikācijai un L-vērtīgas daļēji sakārtotu kopu kategorijas un L-vērtīgas sakārtotu kopu kategorijas konstruēšanai. Darbs sastāv no trim daļām. Pirmajā daļā tiek ievestas visas nepieciešamās definīcijas un teorēmas attiecības definēšanai un kategoriju konstruēšanai, kā arī apskatītas klasisko daļēji sakārtotu kopu kategorijas (POS) un sakārtotu kopu kategorijas (OS) konstrukcijas. Otrajā daļā tiek definēta nestrikta sakārtojuma attiecība un uz tās pamata konstruētas L-vērtīgas POS un OS kategorijas. Trešā daļa ir veltīta nestrikta sakārtojuma attiecībai, kura ir konstruēta nestriktā kopā, kā arī aplūkotas attiecīgas L-vērtīgas POS un OS kat…

Matemātika
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Degree of monotonicity in aggregation process

2010

In this paper we introduce a fuzzy order relation notion in the description of aggregation process. Namely, we use the fuzzy order relation to define the degree of monotonicity, which is equal to 1 for a monotone function with respect to a crisp order relation. In that case, integration of fuzzy order relation allows us to generalize the notion of monotonicity and we try to investigate the benefits of using fuzzy relations instead of a crisp relation. Further we illustrate this definition by examples and study the properties of aggregation functions which have a certain degree of monotonicity.

Discrete mathematicsComputingMethodologies_PATTERNRECOGNITIONDegree (graph theory)Relation (database)Construction industryProcess (engineering)Fuzzy setApplied mathematicsOrder (group theory)Monotonic functionFuzzy logicMathematicsInternational Conference on Fuzzy Systems
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Fuzzy order relations and monotone mappings: categorical constructions and applications in aggregation process

2012

Elektroniskā versija nesatur pielikumus

Nestrikto sakārtojumu teorijaAgregācijas funkcijaL-E-order relationL-valued categoriesMonotonitāteMatemātikaDaudzkriteriāla lineāra programmēšanaL-valued relationsAggregation process
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On t-Conorm Based Fuzzy (Pseudo)metrics

2020

We present an alternative approach to the concept of a fuzzy (pseudo)metric using t-conorms instead of t-norms and call them t-conorm based fuzzy (pseudo)metrics or just CB-fuzzy (pseudo)metrics. We develop the basics of the theory of CB-fuzzy (pseudo)metrics and compare them with “classic” fuzzy (pseudo)metrics. A method for construction CB-fuzzy (pseudo)metrics from ordinary metrics is elaborated and topology induced by CB-fuzzy (pseudo)metrics is studied. We establish interrelations between CB-fuzzy metrics and modulars, and in the process of this study, a particular role of Hamacher t-(co)norm in the theory of (CB)-fuzzy metrics is revealed. Finally, an intuitionistic version of a CB-fu…

Theoretical computer scienceLogicComputer scienceMathematics::General MathematicsCB-fuzzy (pseudo)metric02 engineering and technology01 natural sciencesFuzzy logic0202 electrical engineering electronic engineering information engineeringCB-fuzzy (pseudo)metric; archimedian t-(co)norms; hamacher t-(co)norm; modular; modular metric; intuinionistic fuzzy metricsmodular0101 mathematicsMathematical PhysicsAlgebra and Number Theoryintuinionistic fuzzy metricslcsh:Mathematicslcsh:QA1-939010101 applied mathematicsNorm (mathematics)hamacher t-(co)normmodular metric020201 artificial intelligence & image processingGeometry and TopologyComputingMethodologies_GENERALarchimedian t-(co)normsAnalysisAxioms
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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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