METHOD OF AUTONOMOUSLY CONSTITUTING FUZZY NEURAL NETWORK

PROBLEM TO BE SOLVED: To determine the initial location of membership functions corresponding to the non-linearity of a modeling object. SOLUTION: The calculation process of an inference value based on fuzzy inference is composed of a neural network, a parameter to be identified in the fuzzy inferen...

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Bibliographische Detailangaben
Hauptverfasser:	FUJIME YOKO, YAMAGUCHI MASASHI, FURUHASHI TAKESHI, UCHIKAWA YOSHIKI
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING COUNTING ELECTRIC DIGITAL DATA PROCESSING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING
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Beschreibung
Zusammenfassung:	PROBLEM TO BE SOLVED: To determine the initial location of membership functions corresponding to the non-linearity of a modeling object. SOLUTION: The calculation process of an inference value based on fuzzy inference is composed of a neural network, a parameter to be identified in the fuzzy inference is made correspondent to the coupling load of the neural network and the coupling load is updated by learning so that a fuzzy rule and a membership function can be controlled. In a learning process, the fuzzy rule is autonomously added and deleted and on a fuzzy neural network for acquiring the fuzzy rules of a number required for a controlled system, the number of initial membership functions is determined while using a predetermined evaluation reference.