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

Author

Singh, Lotika ; Kumar, Satish

Author_Institution

Dept. of Phys. & Comput. Sci., Dayalbagh Educ. Inst., Agra

fYear

2007

fDate

5-7 March 2007

Firstpage

282

Lastpage

286

Abstract

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

Keywords

computational complexity; evolutionary computation; fuzzy neural nets; fuzzy reasoning; fuzzy systems; learning (artificial intelligence); parallel algorithms; ASuPFuNIS parallelization strategy; DE learning; asymmetric subsethood product fuzzy-neural inference system; differential evolution learning; island model approach; migration model scheme; parallel evolutionary algorithm; Clustering algorithms; Computer science; Evolutionary computation; Fuzzy neural networks; Fuzzy systems; Master-slave; Message passing; Neural networks; Parallel architectures; Physics;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing: Theory and Applications, 2007. ICCTA '07. International Conference on

Conference_Location

Kolkata

Print_ISBN

0-7695-2770-1

Type

conf

DOI

10.1109/ICCTA.2007.100

Filename

4127382