计算机应用与软件2011，Vol.28Issue(2)：83-86,4.
基于小波变换和支持向量机的水质预测
WATER QUALITY PREDICTION BASED ON WAVELET ANALYSIS AND SUPPORT VECTOR MACHINE
摘要
Abstract
The paper proposes a prediction model of water quality based on wavelet transform and support vector machine (SVM). It uses wavelet to obtain characteristics of water quality time-series at different scales,also uses improved particle swarm optimization (PSO) to optimise three parameters of regressive SVM ,which improves the prediction accuracy. The model is applied to 1-step and 2-step predictions of dissolved oxygen concentration measured at Wangjiangjing automatic monitoring station. The maximum MAPE of 10-group test samples is 4.54％ ,and this is compared with the prediction of BP neural network model. The results show that the model is of good performance,high precision, easy to use and has better prediction effect than the BP neural network model' s, so it is an effective method for water quality prediction .关键词
水质预测/小波分析/支持向量机/粒子群算法/混沌/参数优化引用本文复制引用
梁坚,何通能..基于小波变换和支持向量机的水质预测[J].计算机应用与软件,2011,28(2):83-86,4.基金项目
浙江省重大科技专项(2008C13017-2). （2008C13017-2）
