基于模糊神经网络的大型多辊热连轧产品质量模型

A QUALITY MODEL FOR LARGE-SCALE HOT-STEEL ROLLING PRODUCTION BASED ON FUZZY NEURAL NETWORK

  • 摘要: 本文提出了一种新模糊神经网络及其学习算法.将这种神经网络用作大型多辊热连轧产品质量模型,解决了高维输入数据的建模问题.经过9千多个实测数据建模及检验,测试结果表明,85%的样本的检测值与实测值的误差满足工程实际要求.

     

    Abstract: A kind of FNN and learning algorithm is presented in this paper. The FNN is taken as the model of large-scale hot steel rolling quality and a high-dimensional modeling problem is resolved. After modeling and examination using more than nine thousand of examples, the result of forecast shows that 85% of error value between forest value and real value satisfies the practice engineering demand.

     

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