Efficiency Prediction of Limestone-Gypsum Wet Desulphurization Based on Support Vector Machine

Abstract

This paper studies the prediction of power plant desulfurization efficiency, based on support vector machine through the meshing method for parameter optimization, establish a prediction model, with the running of the actual data to predict the results: mean square error (MSE) is 0.00259324, the correlation coefficient (R) is 0.979927%, the largest error is less than 1.5%, the results show that the established forecast model based on support vector machine (SVM) with high accuracy to predict the desulfurization efficiency, and can satisfy the engineering need of flue gas desulfurization efficiency prediction.