基于不同输入参数的煤灰熔点预测模型及改进方法

Model and Improvement Method of Coal Ash Melting Point Prediction based on Different Input Parameters

为提高煤灰熔点预测精度,采用支持向量机算法,分别建立了以8种煤灰主要成分为输入量的8输入参数模型以及以8种灰成分加5种煤灰熔融性参数为输入的13输入参数模型,用于预测煤灰软化温度,并利用误差补偿方法对13输入参数模型进行了改进。结果显示,13输入参数模型相比8输入参数模型可以缩小灰熔点预测误差区间,尤其使负误差减小;相比于改进前,改进后的13输入参数模型使均方差降低了59.5%。

In order to improve the prediction accuracy of coal ash melting point,the 8-input parameter model with 8 kinds of main coal ash composition as the input and the 13-input parameter model with 8 kinds of ash composition and 5 kinds of coal ash melting parameters as the input were established respectively,to predict coal ash softening temperature.And the 13-input parameter model was improved by the method of error compensation.The results show that the 13-input parameter model can reduce the error range of ash melting point prediction,compared with the 8-input parameter model,especially to reduce the negative error.The improved 13-input parameter model reduces the mean square error by 59.5%,compared with that before the improvement.