Prediction system of sewage outflow COD based on LS-SVM

To solve the multi-variable, nonlinear and large time delay problems in the sewage treatment process, a prediction model of sewage outflow COD based on the Least Square Support Vector Machine (LS-SVM) is proposed. By converting the inequality constraints into equality constraints, the model transforms solving the SVM from a Quadratic Programming (QP) problem to a group of linear equations, which simplifies the learning process and improves the calculating efficiency. Compared with BP neural network, the experimental results verify that LS-SVM method has effectively improved performance in predicting sewage outflow COD. Some researches on empirical application have been done with the monitoring data in a wastewater treatment plant to verify the effectiveness and feasibility of the model.