Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach

I
ICCTA
2007
International Conference on Computing: Theory and Applications (ICCTA'07)
Abstract - Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach

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International Conference on Computing: Theory and Applications (ICCTA'07)

Kolkata, India

March 05-March 07

ISBN: 0-7695-2770-1

	ASCII Text	x
	Lotika Singh, Satish Kumar, "Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach," International Conference on Computing: Theory and Applications, pp. 282-286, International Conference on Computing: Theory and Applications (ICCTA'07), 2007.

	BibTex	x
	@article{ 10.1109/ICCTA.2007.100, author = {Lotika Singh and Satish Kumar}, title = {Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach}, journal ={International Conference on Computing: Theory and Applications}, volume = {0}, year = {2007}, isbn = {0-7695-2770-1}, pages = {282-286}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICCTA.2007.100}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - International Conference on Computing: Theory and Applications TI - Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach SN - 0-7695-2770-1 SP282 EP286 A1 - Lotika Singh, A1 - Satish Kumar, PY - 2007 KW - null VL - 0 JA - International Conference on Computing: Theory and Applications ER -

Lotika Singh, Dayalbagh Educational Institute, Agra

Satish Kumar, Dayalbagh Educational Institute, Agra

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCTA.2007.100

This paper introduces an Island Model approach for differential evolution (DE) learning in Asymmetric Subsethood Product Fuzzy Neural Inference System (ASuPFuNIS). In the island model, each island executes an independent DE and maintains its own sub-population for search. The migration model scheme has been implemented here to parallelize ASuPFuNIS. The parallelization strategy presented here is compared with the master-slave approach.

Citation:

Lotika Singh, Satish Kumar, "Parallel Evolutionary Asymmetric Subsethood Product Fuzzy-Neural Inference System: An Island Model Approach," iccta, pp.282-286, International Conference on Computing: Theory and Applications (ICCTA'07), 2007

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