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Hybrid Neural Network Model for RH Vacuum Refining Process Control 被引量:6
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作者 ZHANGChun-xia WANGBao-jun +4 位作者 ZHOUShi-guang LIULiu XUJing-bo LINLi-ping ZHANGCheng-fu 《Journal of Iron and Steel Research(International)》 SCIE EI CAS CSCD 2004年第1期12-16,共5页
A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and ... A hybrid neural network model,in which RH process(theoretical)model is combined organically with neural network(NN)and case-base reasoning(CBR),was established.The CBR method was used to select the operation mode and the RH operational guide parameters for different steel grades according to the initial conditions of molten steel,and a three-layer BP neural network was adopted to deal with nonlinear factors for improving and compensating the limitations of technological model for RH process control and end-point prediction.It was verified that the hybrid neural network is effective for improving the precision and calculation efficiency of the model. 展开更多
关键词 rh vacuum refining process process control model hybrid neural network
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