Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/29753
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dc.contributor.authorNAPOLES RUIZ, Gonzalo-
dc.contributor.authorSalmeron, Jose L.-
dc.contributor.authorFroelich, Wojciech-
dc.contributor.authorFalcon, Rafael-
dc.contributor.authorEspinosa, Maikel Leon-
dc.contributor.authorVANHOENSHOVEN, Frank-
dc.contributor.authorBello, Rafael-
dc.contributor.authorVANHOOF, Koen-
dc.date.accessioned2019-10-15T14:29:54Z-
dc.date.available2019-10-15T14:29:54Z-
dc.date.issued2020-
dc.identifier.citationCzarnowski, Ireneusz; Howlett, Robert J.; Jain, Lakhmi C. (Ed.). Intelligent Decision Technologies 2019, Springer, Singapore,p. 77-87-
dc.identifier.isbn9789811383106-
dc.identifier.urihttp://hdl.handle.net/1942/29753-
dc.description.abstractFuzzy cognitive maps (FCMs) are knowledge-based neural systems comprised of causal relations and well-defined neural concepts. Since their inception three decades ago, FCMs have been used to model a myriad of problems. Despite the research progress achieved in this field, FCMs are still surrounded by important misconceptions that hamper their competitiveness in several scenarios. In this paper, we discuss some theoretical and practical issues to be taken into account when modeling FCM-based systems. Such issues range from the causality fallacy and the timing component to limited prediction horizon imposed by the network structure. The conclusion of this paper is that the FCM’s theoretical underpinnings need to be revamped in order to overcome these limitations. Closing the gap between FCMs and other neural network models seems to be the right path in that journey-
dc.language.isoen-
dc.publisherSpringer, Singapore-
dc.relation.ispartofseriesSmart Innovation, Systems and Technologies-
dc.rightsSpringer Nature Singapore Pte Ltd. 2020 2019 Springer Nature Switzerland AG. Part of Springer Nature-
dc.titleFuzzy Cognitive Modeling: Theoretical and Practical Considerations-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsCzarnowski, Ireneusz-
local.bibliographicCitation.authorsHowlett, Robert J.-
local.bibliographicCitation.authorsJain, Lakhmi C.-
local.bibliographicCitation.conferencedate17-19/06/2019-
local.bibliographicCitation.conferencenameSmart Digital Futures 2019-
local.bibliographicCitation.conferenceplaceSt George's Bay, St Julians, Malta-
dc.identifier.epage87-
dc.identifier.spage77-
local.bibliographicCitation.jcatC1-
local.publisher.placeSingapore-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
local.relation.ispartofseriesnr142-
dc.identifier.doi10.1007/978-981-13-8311-3_7-
dc.identifier.urlhttps://www.springer.com/gp/book/9789811383106-
local.bibliographicCitation.btitleIntelligent Decision Technologies 2019-
item.fullcitationNAPOLES RUIZ, Gonzalo; Salmeron, Jose L.; Froelich, Wojciech; Falcon, Rafael; Espinosa, Maikel Leon; VANHOENSHOVEN, Frank; Bello, Rafael & VANHOOF, Koen (2020) Fuzzy Cognitive Modeling: Theoretical and Practical Considerations. In: Czarnowski, Ireneusz; Howlett, Robert J.; Jain, Lakhmi C. (Ed.). Intelligent Decision Technologies 2019, Springer, Singapore,p. 77-87.-
item.fulltextWith Fulltext-
item.validationvabb 2022-
item.contributorNAPOLES RUIZ, Gonzalo-
item.contributorSalmeron, Jose L.-
item.contributorFroelich, Wojciech-
item.contributorFalcon, Rafael-
item.contributorEspinosa, Maikel Leon-
item.contributorVANHOENSHOVEN, Frank-
item.contributorBello, Rafael-
item.contributorVANHOOF, Koen-
item.accessRightsRestricted Access-
Appears in Collections:Research publications
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