Paper Info
Title
A comperative study using the methods of simulated annealing and Non-linear Hebbian Learning for Fuzzy Cognitive Maps performances
Abstract
The challenging problem of modelling complex dynamic systems with uncertain environment is reviewed. The theory of Fuzzy Cognitive Maps (FCM), used in recent years to model a good number of systems and applications, is briefly presented. Various methods of FCM learning are presented, specifically the Simulated Annealing (SA) and the Non-linear Hebbian Learning (NHL) methods are analysed in detail. A comperative study between the two methods is performed and presented. The application of SA and NHL on an energy based FCM, leads to interesting results and is motivating for further research and improvement.
Year
DOI
Venue
2016
10.1109/IISA.2016.7785377
2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA)
Keywords
Field
DocType
simulated annealing,nonlinear Hebbian learning,fuzzy cognitive maps,NHL methods,SA,complex dynamic systems
Simulated annealing,Nonlinear system,Computer science,Complex dynamic systems,Fuzzy cognitive map,Hebbian theory,Artificial intelligence,Leabra,Machine learning
Conference
ISSN
ISBN
Citations 
2379-3732
978-1-5090-3430-7
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Eleni S. Vergini130.76
Theodora-Eleni Ch. Kostoula200.34
P. P. Groumpos324614.83