神经网络在水泥生料配料中的应用

Application of Neural Network in Cement Raw Materials Blending System

  • 摘要: 水泥生料配料系统具有多变量、大滞后和非线性的特点 ,采用传统的配料调优方法很难见效。人工神经网络具有很强的非线性映射、特征抽取和容错能力 ,为解决这类问题提供了新的思路。文章根据水泥生料配料的工艺要求 ,采用BP算法建立起能够较好地预测水泥生产质量的神经网络模型 ,以实现生料配料的调优操作。

     

    Abstract: The cement raw materials blending system is very complex for its multi-variable, long time delay and nonlinear characters. It is difficult to set up an exact mathematic model with conventional optimum methods. Artificial neural Networks are able to give new solutions to such problems due to their capacities of nonlinear mapping, character take-out and error tolerance. According to technical requirements of cement raw materials blending, this paper applied neural network model based on BP algorithm to pre-estimate the quality of cement, to realize the optimization of cement raw materials.

     

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