支持向量机灰熔点预测模型研究

Study of a Support Vector Machine-based Model for Predicting Melting Points of Ash

根据电厂对混煤灰熔点计算的需求,采用支持向量机算法和BP神经网络算法对灰熔点进行了建模和对比研究,灰熔点模型采用灰成分作为输入量,灰熔点(ST)作为输出量,用所建模型对单煤和混煤灰熔点进行预测,然后将预测结果与实验结果进行比较。支持向量机模型对单煤和混煤的预测误差分别为0.57%和1.94%,BP神经网络模型对单煤和混煤的预测误差分别为1.925%和10.43%,结果表明,支持向量机模型对单煤和混煤灰熔点的预测更精确。

To the demand of ash melting point calculation of blended coal in power plants,a model for melting points of ash was established and a contrast study was conducted by using the support vector machine algorithm and BP（back propagation） neural network algorithm.The model in question used the ash composition as a input and the melting point of ash as an output.It was employed to predict the ash melting points of a single coal and blended one.Then,the prediction results were compared with the test ones.The errors of the model based on the support vector machine were 0.57% and 1.94 % respectively in predicting the single coal and blended one while those of the model based on the BP neural network were 1.925% and 10.43% respectively in predicting the above-mentioned two types of coal.The research results show that the model based on the support vector machine is more precise when predicting the ash melting points of a single coal and blended one.