WANG Ping
,
HUANG Zhenyi
,
ZHANG Mingya
,
ZHAO Xuewu
钢铁研究学报(英文版)
Mechanical property prediction of hot rolled strip is one of the hotspots in material processing research. To avoid the local infinitesimal defect and slow constringency in pure BP algorithm, a kind of global optimization algorithm—particle swarm optimization (PSO) is adopted. The algorithm is combined with the BP rapid training algorithm, and then, a kind of new neural network (NN) called PSOBP NN is established. With the advantages of global optimization ability and the rapid constringency of the BP rapid training algorithm, the new algorithm fully shows the ability of nonlinear approach of multilayer feedforward network, improves the performance of NN, and provides a favorable basis for further online application of a comprehensive model.
关键词:
particle swarm optimization algorithm;BP neural network;hot continuous rolling strip;mechanical