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

摘要：

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 real-time. The system was used in the sewage treatment plant. The experimental results prove that this system is feasible.

关键词： regression support vector machine sewage treatmen flocculation process optimized control.

作者: Jingwen Tian Meijuan Gao Yujuan Xiang

作者单位: Beijing Union University, Beijing, china;Beijing University of Chemical Technology Beijing, china Beijing University of Chemical Technology Beijing, china

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 1487-1491

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）