王邦文, 杨光, 徐峰, 李谋谓, 刘圣明, 王国平. 基于人工神经网络铝箔轧机轧制力模型[J]. 工程科学学报, 1997, 19(2): 173-177. DOI: 10.13374/j.issn1001-053x.1997.02.012
引用本文: 王邦文, 杨光, 徐峰, 李谋谓, 刘圣明, 王国平. 基于人工神经网络铝箔轧机轧制力模型[J]. 工程科学学报, 1997, 19(2): 173-177. DOI: 10.13374/j.issn1001-053x.1997.02.012
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Wang Bangwen, Yang Guang, Xu Feng, Li Mouwei, Liu Shengming, Wang Guoping. Model of Aluminium Foil Rolling Force Based on Neural Networks[J]. Chinese Journal of Engineering, 1997, 19(2): 173-177. DOI: 10.13374/j.issn1001-053x.1997.02.012
Citation: Wang Bangwen, Yang Guang, Xu Feng, Li Mouwei, Liu Shengming, Wang Guoping. Model of Aluminium Foil Rolling Force Based on Neural Networks[J]. Chinese Journal of Engineering, 1997, 19(2): 173-177. DOI: 10.13374/j.issn1001-053x.1997.02.012
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基于人工神经网络铝箔轧机轧制力模型

Model of Aluminium Foil Rolling Force Based on Neural Networks

    摘要
  • 摘要: 采用BP神经网络原理对1350mm铝箔轧机轧制数据重新处理，建立了基于人工神经网络的轧制力模型.结果表明，用人工神经网络轧制力模型的计算值与实测值相比较偏差<3%.该模型较真实地反映了轧制过程的特征.

     

    Abstract: Based on the principle of BP neural networks, the rolling force model is established after thoroughly analyzing and reprocessing the data of 1350 mm aluminium foil mill. It states that the difference between the output of artificial neural networks rolling force model and the real value is in the order of 3 percent. The model reflects the real feature of process.

     

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