Design methodology of optimized IG_gHSOFPNN and its application to pH neutralization process

Authors:
Ho-Sung Park;Kyung-Won Jang;Sung-Kwun Oh;Tae-Chon Ahn
Affiliations:
School of Electrical Electronic and Information Engineering, Wonkwang University, Shinyong-Dong, Iksan, Chon-Buk, South Korea;School of Electrical Electronic and Information Engineering, Wonkwang University, Shinyong-Dong, Iksan, Chon-Buk, South Korea;Department of Electrical Engineering, The University of Suwon, Bongdam-eup, Hwaseong-si, Gyeonggi-do, South Korea;School of Electrical Electronic and Information Engineering, Wonkwang University, Shinyong-Dong, Iksan, Chon-Buk, South Korea
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

Citing 5
Cited 0

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Abstract

In this paper, we propose design methodology of optimized Information granulation based genetically optimized Hybrid Self-Organizing Fuzzy Polynomial Neural Networks (IG_gHSOFPNN) by evolutionary optimization. The augmented IG_gHSOFPNN results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HSOFPNN. The GA-based design procedure being applied at each layer of IG_gHSOFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HSOFPNN. The obtained results demonstrate superiority of the proposed networks over the existing fuzzy and neural models.