Dynamic Node Creation in Backpropagation Networks
作者:
TIMUR ASH,
期刊:
Connection Science
(Taylor Available online 1989)
卷期:
Volume 1,
issue 4
页码: 365-375
ISSN:0954-0091
年代: 1989
DOI:10.1080/09540098908915647
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper introduces a new method called Dynamic Node Creation (DNC) which automatically grows BP networks until the target problem is solved. DNC sequentially adds nodes one at a time to the hidden layer(s) of the network until the desired approximation accuracy is achieved. Simulation results for parity, symmetry, binary addition, and the encoder problem are presented. The procedure was capable of finding known minimal topologies in many cases, and was always within three nodes of the minimum. Computational expense for finding the solutions was comparable to training normal BP networks with the same final topologies. Starting out with fewer nodes than needed to solve the problem actually seems to help find a solution. The method yielded a solution for every problem tried.
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