Self-Organizing Hybrid Neurofuzzy Networks

Abstract. We introduce a concept of self-organizing Hybrid Neurofuzzy Networks (HNFN), a hybrid modeling architecture combining neurofuzzy (NF) and polynomial neural networks(PNN). The development of the Self-organizing HNFN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the Self-organizing HNFN results from a synergistic usage of NF and PNN. NF contribute to the formation of the premise part of the rule-based structure of the Self-organizing HNFN. The consequence part of the Self-organizing HNFN is designed using Self-organizing PNN. We also distinguish between two types of the Self-organizing HNFN architecture showing how this taxonomy depends on connection points. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process and to get output performance with superb predictive ability. The performance of the Self-organizi...

• Type: Conference
• Year: 2003
• Where: ICCS
• Authors: Sung-Kwun Oh, Su-Chong Joo, Chang-Won Jeong, Hyun-Ki Kim
• Keywords: ICCS 2003, Self-organizing HNFN, Self-organizing HNFN Architecture, Self-organizing HNFN Dwells