Design of Advanced Self-Organizing Fuzzy Polynomial Neural Networks Based on FPN by Evolutionary Algorithms

진화론적 알고리즘에 의한 퍼지 다항식 뉴론 기반 고급 자기구성 퍼지 다항식 뉴럴 네트워크 구조 설계

In this paper, we introduce the advanced Self-Organizing Fuzzy Polynomial Neural Network based on optimized FPN by evolutionary algorithm and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed model gives rise to a structurally and parametrically optimized network through an optimal parameters design available within Fuzzy Polynomial Neuron(FPN) by means of GA. Through the consecutive process of such structural and parametric optimization, an optimized and flexible the proposed model is generated in a dynamic fashion. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.