Ignition characteristic prediction model for blending coal based on least squares support vector machine

Least squares support vector machine method was adopted in the model of analysing the igniting characteristic of powered coal.In order to solve the problem of difficult to calculate the igniting temperature,the model was established and was following optimized by particle swarm optimization(PSO) .This model overcomes the over fitting of neural network algorithm,and weak generalization shortcomings on the one hand;increases the calculation speed of the solution process on the other hand.Experimental results show least squares support vector machine method gets the mean square error of prediction of 8.60,and the correlation coefficient of 0.93,which has high precise.Therefore,using least squares support vector machine can achieve a more accurate prediction ignition temperature of coal blending.