Wastewater treatment prediction based on immune optimization multi-output least squares support vector regression machine

Abstract

In order to improve effluent water quality prediction precision of wastewater treatment system, the main factors which have influence on the effluent quality are analyzed. Wastewater treatment system is a multi-input multi-output system. But the traditional support vector regression machine (SVRM) algorithms are only used for single-output systems. If several SVRM models are constructed for multi-input multi-output systems, it will increase the complexity of the algorithm and the precision is poor for the correlation of output variables. In order to solve prediction problem of multi-output system, a method of multi-output least squares support vector regression machine (LS-SVRM) based on immune optimization is proposed in this study. The multi-output LS-SVRM is used to predict effluent quality, using the immune algorithm to optimize the parameters of the multi-output LS-SVRM. Simulation shows that the proposed method has a better prediction precision for wastewater treatment system.