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Mechanical Property Prediction of Strip Model Based on PSOBP Neural Network

WANG Ping , HUANG Zhenyi , ZHANG Mingya , ZHAO Xuewu

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 PSOBP 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 online application of a comprehensive model.

关键词: particle swarm optimization algorithm;BP neural network;hot continuous rolling strip;mechanical

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