FuNN - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition
نویسنده
چکیده
Fuzzy neural networks have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the form of semantically meaningful fuzzy rules, and the ability to accommodate both data and existing expert knowledge about the problem under consideration. This paper investigates adaptive learning, rule extraction and insertion, and neural/fuzzy reasoning for a particular model of a fuzzy neural network called FuNN. As well as providing for representing a fuzzy system with an adaptable neural architecture, FuNN also incorporates genetic algorithms as one of its adaptation strategies.
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FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition
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