Intelligent Optimized Control of Flocculation Process of Sewage Treatment Based on Support Vector Machine

The flocculating process of sewage treatment is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The support vector machine (SVM) has the ability of strong nonlinear function approach, it has the ability of strong generalization and it also has the feature of global optimization. Here, a intelligent optimized control system based on regression SVM is presented, moreover, we propose a self-adaptive parameter adjust iterative algorithm to confirm SVM parameters. In this system, the parameters of flocculation process were measured using sensors, then the control system can control the flocculation process realtime. The system was used in the sewage treatment plant. The experimental results prove that this system is feasible