DocumentCode
3347033
Title
A hybrid method using PSO and NHL algorithms to train Fuzzy Cognitive Maps
Author
Yazdi, Mohsen Najafi ; Lucas, Caro
Author_Institution
ECE Sch., Univ. of Tehran, Tehran
Volume
3
fYear
2008
fDate
6-8 Sept. 2008
Abstract
In this paper a new hybrid method for training fuzzy cognitive maps is presented. FCMs are based on the knowledge of human experts and may not be accurate enough because of probable mistakes of experts. Thus, some learning methods have been investigated to train FCMs, so that these probable mistakes are covered. Two learning methods, PSO and NHL, and a new hybrid of them are introduced and implemented and tested for a chemical control problem.
Keywords
Hebbian learning; cognitive systems; expert systems; fuzzy set theory; particle swarm optimisation; NHL algorithm; PSO algorithm; chemical control problem; fuzzy cognitive maps; human experts; learning methods; Chemical industry; Collision mitigation; Decision making; Fuzzy cognitive maps; Humans; Hybrid intelligent systems; Learning systems; Power system modeling; Steady-state; Testing; Fuzzy Cognitive Maps; Learning Algorithms; Nonlinear Hebbain Rule; Particle Swarm Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2008. IS '08. 4th International IEEE Conference
Conference_Location
Varna
Print_ISBN
978-1-4244-1739-1
Electronic_ISBN
978-1-4244-1740-7
Type
conf
DOI
10.1109/IS.2008.4670458
Filename
4670458
Link To Document