Wastewater Treatment Prediction Based on Chaos-GA Optimized LS-SVM

摘要：

Wastewater treatment is a complicated biochemical process with nonlinearity and time-delay. Its mathematical model is difficult to establish. In order to optimize the process control and reduce the power energy consumption, parameters such as Chemical Oxygen Demand (COD) should be accurately predicted. A novel least square support vector machine model is presented to predict the effluent COD in this paper. A multi-scale chaos search algorithm was proposed to optimize the model parameters, and the genetic algorithm was combined to accelerate the search speed. Simulation results show that the proposed method has higher precision, greater generalization ability and less computation. The prediction MSE was reduced from 21.43 by ANN to 6.83 by the proposed method.

关键词： Wastewater treatment Chemical oxygen demand support vector machine chaos search genetic algorithm

作者: CHEN Zhi-ming HU Jue

作者单位: with the Department of Electronic Science,Huizhou University,Huizhou,China

会议类型: 国际会议

会议名称: 2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)

会议地点: 四川绵阳

会议语种:英文

页码: 4021-4024

在线出版日期: 2011-05-23（万方平台首次上网日期，不代表论文的发表时间）