Guidelines for the selection of network architecture
William C. Carpenter, Margery E. Hoffman · Artificial intelligence for engineering design analysis and manufacturing · 1997
Abstract This paper is concerned with presenting guidelines to aide in the selection of the appropriate network architecture for back-propagation neural networks used as approximators. In particular, its goal is to indicate under what circumstances neural networks should have two hidden layers and under what circumstances they should have one hidden layer. Networks with one and with two hidden layers were used to approximate numerous test functions. Guidelines were developed from the results of these investigations.