Title :
PASS: a program for automatic structure search
Author :
Chen, Zhanbo ; Xiao, Jing ; Cheng, Jie
Author_Institution :
Dept. of Comput. Sci., North Carolina Univ., Charlotte, NC, USA
Abstract :
We utilized the heuristic knowledge gained from a vast number of experiments on using feedforward neural networks (FNNs) to approximate highly nonlinear real-valued functions and developed a program for automatic search of FNNs based on evolutionary computation techniques, called PASS (program for automatic structure search). PASS has been successfully tested in an industrial application-finding FNNs to approximate the mappings between automobile engine control variables and performance parameters. It has shown the promise to be a general and efficient tool for automatic determination of FNNs for real-valued function approximation
Keywords :
Newton method; backpropagation; feedforward neural nets; function approximation; genetic algorithms; internal combustion engines; multilayer perceptrons; neural net architecture; search problems; automatic structure search; automobile engine control; evolutionary computation techniques; feedforward neural networks; heuristic knowledge; highly nonlinear real-valued functions; Automatic control; Automobiles; Engines; Evolutionary computation; Feedforward neural networks; Function approximation; Fuzzy control; Industrial control; Neural networks; Testing;
Conference_Titel :
Neural Networks,1997., International Conference on
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.611684
