Neuro-fuzzy Systems: Review and Prospects

This paper reviews neuro-fuzzy systems, which combine methods from neural network theory with fuzzy systems. Such combinations have been considered for several years already. However, the term neuro-fuzzy still lacks proper deenition, and still has the avour of a buzzword to it. Surprisingly few neuro-fuzzy approaches do actually employ neural networks, even though they are very often depicted in form of some kind of neural network structure. However, all approaches display some kind of learning capability, as it is known from neural networks. This means, they use algorithms which enable them to determine their parameters from training data in an iterative process. In this paper we review some of our neuro-fuzzy approaches to illustrate our view of neuro-fuzzy techniques and our understanding on how these approaches should be used. From our point of view neuro-fuzzy means using heuristic learning strategies derived from the domain of neural network theory to support the development of a fuzzy system.