Neural Networks and Neuro-Fuzzy Systems
Danuta Rutkowska · Studies in fuzziness and soft computing · 2002
This chapter presents an overview of neural networks and neuro-fuzzy systems . The latter are a fusion of neural networks and fuzzy techniques, introduced in [293], initially developed in [66], [408], [87], and then in [167], [166], [491], [273], [169], [157], [228], [503], [270], and others. Neuro-fuzzy systems have been applied in many consumer products [492], [493]. They incorporate some merits of both neural networks and fuzzy systems . In the neuro-fuzzy combinations we distinguish fuzzy neural networks (see Section 3.2), obtained by introducing fuzziness directly into neural networks [169], and fuzzy inference neural networks (see Section 3.3), which are representations of fuzzy systems in the form of connectionist networks [513], similar to neural networks. Of course, different types of neuro-fuzzy systems can be found in the literature, e.g. [493], [300], [53], [162], [361], [243], [347], [582], [229], [223], [496], [244], [56], [141], [101]. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.