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[66780] Artykuł: An Evolutionary Algorithm Based on Graph Theory Metrics for Fuzzy Cognitive Maps LearningCzasopismo: Lecture Notes in Computer Science - Theory and Practice of Natural Computing. TPNC 2017. Tom: 10687, Strony: 137-149ISSN: 1611-3349 ISBN: 978-3-319-71069-3 Wydawca: SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND Opublikowano: 2017 Seria wydawnicza: Lecture Notes in Computer Science Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Materiały z konferencji międzynarodowej (zarejestrowane w Web of Science) Punkty MNiSW: 15 Klasyfikacja Web of Science: Proceedings Paper ![]() ![]() ![]() Keywords: Fuzzy cognitive maps  Evolutionary learning  Graph theory metrics  |
Fuzzy cognitive map (FCM) is an effective tool for modeling dynamic decision support systems. It describes the analyzed phenomenon in the form of key concepts and causal connections between them. The main aspect of building of the FCM model is concepts selection. It is usually based on the expert knowledge. The aim of this paper is to introduce a new evolutionary algorithm for fuzzy cognitive maps learning. The proposed approach allows to select key concepts based on graph theory metrics and determine the connections between them. A simulation analysis was done with the use of synthetic and real-life data.