期刊
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
卷 178, 期 1-3, 页码 19-23出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jmatprotec.2005.07.002
关键词
diameter error compensation; particle swarm optimization; multi-layer feed-forward neural network; sum of squares error (SSE)
This paper presents a particle swarm optimization (PSO) technique in training a multi-layer feed-forward neural network (MFNN) which is used for a prediction model of diameter error in a boring machining. Compared to the back propagation (BP) algorithm, the present algorithm achieves better machining precision with a fewer number of iterations. (c) 2006 Published by Elsevier B.V.
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