Research progress on prediction methods of coal ash melting temperature

In order to predict coal ash melting temperature,the present situation of ash melting temperature prediction model at home and abroad was introduced,including regression analysis method,BP neural network method,support vector machine( SVM) method and FactSage software method. The application of regression analysis method was widely used,the correlation coefficient of predicting formula fitted by the least square method was higher,while its adaptability was poorer. The adaptability of BP neural network was stronger,but the large amounts of data must be input for training the model. The SVM method was better than the first two,but it couldn't clarify the ash melting process of mineral evolution law,that meant it couldn't scientificly indicate ash melting characteristics change mechanism. Fact Sage software method had higher prediction accuracy,it could clarify the process of mineral ash fusion conversion and optimize the ash melting temperature of evaluation criteria. Based on the properties of Fact Sage software method,a more reliable prediction model could be established.