RBF神经网络预测焦化企业煤气产量

Radial Basis Function Neural Network for Gas Output Prediction in Coking Industry

对焦炉的发生和消耗特性进行分析,找出影响煤气产量的主要影响因素,并建立径向基函数(RBF)神经网络模型进行预测,实验表明:RBF模型具有较强的非线性逼近能力,能较真实地反映煤气产量和影响因素之间的非线性关系,预测效果要优于BP神经网络模型。

The characteristics of process of gas production and consumption were analyzed to identify main fac- tors which influencing gas production and to build mathematical model based on these factors to predict gas output. The experimental results show that RBF neural network has very strong nonlinear approximation abili- ty. It can reflect nonlinear relationship between gas production and influential factors.