A new integrated forcasting model for calorific value of coal has been established based on multi-linear regression and least square support vector machine(LS-SVM)

and steps for establishing the said model and the concrete algorithm being given.considering the relationship between the practical calorific value of fuel coal Qb

ad and the industrial analysis data(Wad

Ad

Vdaf)

the integrated model is composed of two parts

mamely the preliminary sub-model and the error correction sub-model.The process of modelling is as in the following:firstly

the sample sets to be constructed by using the ofviginal data

then

the preliminary forcasting is obtained by a multivariate linear regression algorithm

and finally the compensated error is obtained from correction sub-model based on LS-SVM

so the prediction value will be the output value of the preliminary forecasting sub-model plus the compensated error.The practical prediction results show the intgrated model can obviously improve the prediction precision compared to other algorithms

being less time-comsuming

and effectiveness of prediction being superior than other commonly used methods

having certain applying value.