0000000000587383

AUTHOR

Māris Krastiņš

showing 2 related works from this author

Gradation of Fuzzy Preconcept Lattices

2021

Noticing certain limitations of concept lattices in the fuzzy context, especially in view of their practical applications, in this paper, we propose a more general approach based on what we call graded fuzzy preconcept lattices. We believe that this approach is more adequate for dealing with fuzzy information then the one based on fuzzy concept lattices. We consider two possible gradation methods of fuzzy preconcept lattice—an inner one, called D-gradation and an outer one, called M-gradation, study their properties, and illustrate by a series of examples, in particular, of practical nature.

Theoretical computer scienceLogicComputer scienceMathematics::General Mathematicsfuzzy context; fuzzy preconcept; fuzzy preconcept lattice; fuzzy concept; fuzzy concept lattice; graded fuzzy preconcept lattice0206 medical engineeringfuzzy preconceptContext (language use)02 engineering and technologyFuzzy logic0202 electrical engineering electronic engineering information engineeringFuzzy conceptMathematical Physicsfuzzy preconcept latticeAlgebra and Number TheorySeries (mathematics)lcsh:Mathematicsfuzzy contextfuzzy conceptfuzzy concept latticelcsh:QA1-939graded fuzzy preconcept latticeComputer Science::Programming Languages020201 artificial intelligence & image processingGradationGeometry and Topology020602 bioinformaticsAnalysisAxioms; Volume 10; Issue 1; Pages: 41
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On Aggregation of Risk Levels Using T-Conorms

2019

This paper deals with solutions for numeric evaluation of risks containing several different risk factors assessed by experts. The proposed methods can be used to assess the risks and obtain the risk scores in different industries, including financial industry, but they are also suitable for assessing risks in other areas, e.g. project management. While risk is usually considered as a function of probability and impact with strong quantitative background, there are many practical cases when only qualitative risk assessment based on expert opinions can be used. At the same time there are still requirements and needs for applying numerical values and mathematical models to such qualitative as…

Risk levelFramingham Risk ScoreMathematical modelbusiness.industryComputer sciencemedia_common.quotation_subject02 engineering and technologyRisk analysis (engineering)020204 information systems0202 electrical engineering electronic engineering information engineeringProject managementbusinessRisk assessmentFunction (engineering)Financial servicesmedia_common
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