Multivariate relationship modeling using nested fuzzy cognitive map

Motlagh, O. and Papageorgiou, E.l. and Tang, S.H. and Zamberi Jamaludin, (2014) Multivariate relationship modeling using nested fuzzy cognitive map. Sains Malaysiana, 43 (11). pp. 1781-1790. ISSN 0126-6039


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Soft computing is an alternative to hard and classic math models especially when it comes to uncertain and incomplete data. This includes regression and relationship modeling of highly interrelated variables with applications in curve fitting, interpolation, classification, supervised learning, generalization, unsupervised learning and forecast. Fuzzy cognitive map (FCM) is a recurrent neural structure that encompasses all possible connections including relationships among inputs, inputs to outputs and feedbacks. This article examines a new methods for nonlinear multivariate regression using fuzzy cognitive map. The main contribution is the application of nested FCM structure to define edge weights in form of meaningful functions rather than crisp values. There are example cases in this article which serve as a platform to modelling even more complex engineering systems. The obtained results, analysis and comparison with similar techniques are included to show the robustness and accuracy of the developed method in multivariate regression, along with future lines of research.

Item Type:Article
Keywords:Nested fuzzy cognitive map; neural activation; regression
Journal:Sains Malaysiana
ID Code:8051
Deposited By: ms aida -
Deposited On:16 Nov 2014 19:19
Last Modified:14 Dec 2016 06:46

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