Title :
The fast neural network solution for problems based on slow genetic algorithm solutions
Author :
Wang, Yan ; Lu, Yilong
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper presents a study of using radial basis function neural network, that is trained by a finite number of off-line slow genetic algorithm solutions, for infinite number of fast approximate solutions. This approach makes powerful yet slow genetic algorithm solutions possible for real time problems
Keywords :
approximation theory; genetic algorithms; radial basis function networks; fast approximate solutions; genetic algorithm solutions; neural network solution; radial basis function neural network; real time problems; Array signal processing; Feedforward neural networks; Genetic algorithms; Genetic engineering; Multi-layer neural network; Neural networks; Power engineering and energy; Radial basis function networks; Software design; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004509
