OPTIMAL FUEL LOADING PATTERN DESIGN USING AN ARTIFICIAL NEURAL-NETWORK AND A FUZZY RULE-BASED SYSTEM
作者： Han Gon Kim , Soon Heung Chang , Byung Ho Lee
关键词: Control theory 、 Membership function 、 Artificial neural network 、 Neuro-fuzzy 、 Fuzzy rule 、 Fuzzy logic 、 Heuristic 、 Computer science 、 Hybrid system 、 Backpropagation
摘要: The Optimal Fuel Shuffling System (OFSS) was developed for the optimal design of pressurized water reactor (PWR) fuel loading patterns. An pattern is defined in which local power peaking factor lower than a predetermined value during one cycle and effective multiplication maximized to extract maximum energy. OFSS hybrid system rule-based system, fuzzy logic, an artificial neural network (ANN) are connected with each other. classifies patterns into two types by using several heuristic rules rule. rule introduced achieve more faster search. Its membership function automatically updated accordance prediction results. ANN predicts core parameters generated from system. A back propagation used fast parameters. logic can be improve capabilities existing algorithms. demonstrated validated 1 Kori-1 PWR.
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