A New Learning Algorithm of Neuro-Fuzzy Modeling Using Self-Constructed Clustering

다국어 초록 (Multilingual Abstract)

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Proposed Clustering Algorithm
• 3. Proposed Neuro-Fuzzy Model and Learning (Modeling)
• 4. Simulation Results
• 5. Conclusions
• References