Water Quality Prediction of Changjiang of Jingdezhen through Particle Swarm Optimization Algorithm

摘要：

In order to obtain the water quality trend of Changjiang of Jingdezhen and prevent water pollution events, a water quality prediction model is built. Water quality index data, which are observed from a section of Changjiang, are taken as training samples. And eight indexes are selected, such as PH, chloride, sulfate, dissolved oxygen (DO), ammonia, permanganate, iron, total phosphorus (TP). Radial basis function (RBF) neural network model is optimized by particle swarm optimization (PSO) algorithm, and then the model is used to predict water quality indexes of Changjiang. The experimental results indicate that the deviation of predicted values calculated by the model and observed values are almost less then 4%, and we could infer that RBF neural network model optimized by PSO is a reliable and effective method for water quality prediction.

作者: Xing Xu Na Hu Bingxiang Liu

作者单位: College of Information and Engineering, Jingdezhen Ceramic Institute, Jingdezhen Jiangxi 333403, China

会议类型: 国际会议

会议名称: International Conference on Management and Service Science(2011年第五届管理与服务科学国际会议 MASS 2011)

会议地点: 武汉

会议语种:英文

页码: 1-4

在线出版日期: 2011-08-12（万方平台首次上网日期，不代表论文的发表时间）