Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/28903
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dc.contributor.authorPoczeta, Katarzyna-
dc.contributor.authorKubus, Lukasz-
dc.contributor.authorYastrebov, Alexander-
dc.contributor.authorPAPAGEORGIOU, Elpiniki-
dc.date.accessioned2019-08-07T12:54:55Z-
dc.date.available2019-08-07T12:54:55Z-
dc.date.issued2018-
dc.identifier.citationFidanova, S (Ed.). RECENT ADVANCES IN COMPUTATIONAL OPTIMIZATION, WCO 2016, SPRINGER-VERLAG BERLIN,p. 153-175-
dc.identifier.isbn9783319598604-
dc.identifier.issn1860-949X-
dc.identifier.urihttp://hdl.handle.net/1942/28903-
dc.description.abstractFuzzy cognitive map (FCM) is a universal tool for modeling dynamic decision support systems. It can be constructed by the experts or learned based on historical data. FCM models learned from data are denser than those created by humans. We developed an evolutionary learning approach for fuzzy cognitive maps based on density and system performance indicators. It allows to select only the most significant connections between concepts and receive the structure more similar to the FCMs initialized by experts. This paper is devoted to the application of the developed approach to model decision support systems with the use of real-life and historical data.-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.relation.ispartofseriesStudies in Computational Intelligence-
dc.rightsSpringer International Publishing AG 2018-
dc.titleApplication of Fuzzy Cognitive Maps with Evolutionary Learning Algorithm to Model Decision Support Systems Based on Real-Life and Historical Data-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsFidanova, S-
local.bibliographicCitation.conferencedateSEP 11-14, 2016-
local.bibliographicCitation.conferencename9th International Workshop on Computational Optimization (WCO)-
local.bibliographicCitation.conferenceplaceGdansk, POLAND-
dc.identifier.epage175-
dc.identifier.spage153-
dc.identifier.volume717-
local.format.pages23-
local.bibliographicCitation.jcatC1-
dc.description.notes[Poczeta, Katarzyna; Kubus, Lukasz; Yastrebov, Alexander] Kielce Univ Technol, Al Tysiaclecia Panstwa Polskiego 7, PL-25314 Kielce, Poland. [Papageorgiou, Elpiniki I.] Technol Educ Inst TEI Cent Greece, 3rd Km Old Natl Rd Lamia Athens, Lamia 35100, Greece. [Papageorgiou, Elpiniki I.] Hasselt Univ, Fac Business Econ, Campus Diepenbeek Agoralaan Gebouw D, B-3590 Diepenbeek, Belgium.-
local.publisher.placeBERLIN-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1007/978-3-319-59861-1_10-
dc.identifier.isi000451672900010-
local.bibliographicCitation.btitleRECENT ADVANCES IN COMPUTATIONAL OPTIMIZATION, WCO 2016-
item.validationecoom 2019-
item.contributorPoczeta, Katarzyna-
item.contributorKubus, Lukasz-
item.contributorYastrebov, Alexander-
item.contributorPAPAGEORGIOU, Elpiniki-
item.fulltextWith Fulltext-
item.accessRightsRestricted Access-
item.fullcitationPoczeta, Katarzyna; Kubus, Lukasz; Yastrebov, Alexander & PAPAGEORGIOU, Elpiniki (2018) Application of Fuzzy Cognitive Maps with Evolutionary Learning Algorithm to Model Decision Support Systems Based on Real-Life and Historical Data. In: Fidanova, S (Ed.). RECENT ADVANCES IN COMPUTATIONAL OPTIMIZATION, WCO 2016, SPRINGER-VERLAG BERLIN,p. 153-175.-
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