Title :
Using a genetic algorithm to evolve an optimum input set for a predictive neural network
Author :
Weller, P.R. ; Summers, R. ; Thompson, A.C.
Author_Institution :
City Univ., London, UK
Abstract :
This paper describes an investigation into using a genetic algorithm to evolve the optimum set of inputs for a neural network. The network is to be used in a novel way for the prediction of nuclear reactor parameters under fault conditions. The development of transients is calculated in a recursive manner. The previous work and the next stage of research are described. The procedure and genetic algorithm options, including fitness, are discussed along with explanations. Finally an outline of the remaining work is introduced
Keywords :
expert systems; fission reactor operation; fission reactor safety; genetic algorithms; neural nets; nuclear engineering computing; parameter estimation; fitness; genetic algorithm; nuclear reactor parameters; predictive neural network; transients;
Conference_Titel :
Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)
Conference_Location :
Sheffield
Print_ISBN :
0-85296-650-4
DOI :
10.1049/cp:19951058
