Abstract
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 on-line application of a comprehensive model.
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Foundation Item: Item Sponsored by Natural Science Foundation of Anhui Provincial Education Department of China (2006KJ080A)
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Wang, P., Huang, Zy., Zhang, My. et al. Mechanical Property Prediction of Strip Model Based on PSO-BP Neural Network. J. Iron Steel Res. Int. 15, 87–91 (2008). https://doi.org/10.1016/S1006-706X(08)60132-6
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DOI: https://doi.org/10.1016/S1006-706X(08)60132-6