A Self-Organizing Neural Fuzzy Inference Network

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Venue:
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
Year:
2000

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Abstract

A self-organizing neural network is proposed which is inherently a fuzzy inference system with the capability of learning fuzzy rules from data. The learning strategy consists of two phases: a self-organizing clustering to establish the structure of the network as well as the initial values of its parameters and a supervised learning phase for optimal adjustment of these parameters. After learning, the network encodes in its structure the essential design parameters of a fuzzy system. An example is given to illustrate the characteristics and capabilities of the proposed network.