文章基本信息

标题：Development of Genetic Algorithm based Neural Network model for parameter estimation of Fast Breeder Reactor Subsystem
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作者：Subhra Rani Patra ; R. Jehadeesan ; S. Rajeswari 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：4
页码：87-90
出版社：International Journal of Soft Computing & Engineering
摘要：This work provides the construction of Genetic Algorithm based Neural Network for parameter estimation of Fast Breeder Test Reactor (FBTR) Subsystem. The parameter estimated here is temperature of Intermediate Heat Exchanger of Fast Breeder Test Reactor. Genetic Algorithm based Neural Network is a global search algorithm having less probability of being trapped in local minimum problem as compared to Standard Back Propagation algorithm which is a local search algorithm. The various development stages of Genetic Algorithm based Neural Network such as the preparation of the training set, weight extraction from the genetic population, training of the neural network and validation phase etc have been described in detail.
关键词：Genetic Algorithm based Neural Network; Fast;Breeder Test Reactor; Intermediate Heat Exchanger; Multi layer;Perceptron