%0 Conference Proceedings
%T A Study on Fuzzy Cognitive Map Optimization Using Metaheuristics
%+ Warsaw University of Technology [Warsaw]
%+ University of Bialystok
%A Cisłak, Aleksander
%A Homenda, Władysław
%A Jastrzębska, Agnieszka
%Z Part 8: Intelligent Distributed Systems
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM)
%C Vilnius, Lithuania
%Y Khalid Saeed
%Y Władysław Homenda
%I Springer International Publishing
%3 Computer Information Systems and Industrial Management
%V LNCS-9842
%P 577-588
%8 2016-09-14
%D 2016
%R 10.1007/978-3-319-45378-1_51
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X Fuzzy Cognitive Maps (FCMs) are a framework based on weighted directed graphs which can be used for system modeling. The relationships between the concepts are stored in graph edges and they are expressed as real numbers from the $$[-1,1]$$ interval (called weights). Our goal was to evaluate the effectiveness of non-deterministic optimization algorithms which can calculate weight matrices (i.e. collections of all weights) of FCMs for synthetic and real-world time series data sets. The best results were reported for Differential Evolution (DE) with recombination based on 3 random individuals, as well as Particle Swarm Optimization (PSO) where each particle is guided by its neighbors and the best particle. The choice of the algorithm was not crucial for maps of size roughly up to 10 nodes, however, the difference in performance was substantial (in the orders of magnitude) for bigger matrices.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01637479/document
%2 https://inria.hal.science/hal-01637479/file/419526_1_En_51_Chapter.pdf
%L hal-01637479
%U https://inria.hal.science/hal-01637479
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-9842