Publication | Closed Access
Composition methods of fuzzy neural networks
31
Citations
1
References
2002
Year
Unknown Venue
Artificial IntelligenceFuzzy SystemsMachine LearningFuzzy ControlNeural Networks (Machine Learning)Fuzzy Neural NetworksEngineeringFuzzy ModelingIntelligent SystemsSocial SciencesSystems EngineeringFuzzy Natural Language ProcessingComposition MethodsFuzzy Pattern RecognitionFuzzy LogicFuzzy ComputingFuzzy RulesNeural Networks (Computational Neuroscience)Computer ScienceNeural NetworksFuzzy Inference SystemsNeuro-fuzzy SystemFuzzy Expert System
Fuzzy neural networks (FNNs) are systems which apply neural networks to fuzzy reasoning. Two types of FNN are presented. In the first type, the consequences of fuzzy reasoning are realized by constants. In the second type, the consequences are expressed by first-order linear equations. The FNNs can automatically identify fuzzy rules and tune membership functions. Their performance on fuzzy reasoning is examined by simulations. The features of the two types of FNNs are clarified.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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