Study of Short-term Water Quality Prediction Model Based on PSo-wSVR

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Study of Short-term Water Quality Prediction Model Based on PSo-wSVR

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[1]XU Long-qin,LIU Shuang-vin.Study of Short-term Water Quality Prediction Model Based on PSo-wSVR[J].Journal of Zhengzhou University (Engineering Science),2013,34(03):112-116.[doi:10.3969/j.issn.1671-6833.2013.03.027]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 34 Number of periods: 2013 03 Page number: 112-116 Column: Public date: 2013-05-31

Title:: Study of Short-term Water Quality Prediction Model Based on PSo-wSVR

Author(s):: XU Long-qin1; LIU Shuang-vin1; 2; 3; 1.School of Information ，Guangdong Ocean Universit , Zhanjiang 524025，China; 2.Key Laboratory of Modern Precision Agri-culture System Integration Research of Ministry of Education , China Agriculural University ,Beijing 100083 , China;3.Beijing En-gineering Research Center for Agricultural Internet of Things，China Agricultural University，Beijing 100083,China

Keywords:: water quality prediction; weighted support vector regression; particle swarm optimization; parameters optimization

CLC:: X83

DOI:: 10.3969/j.issn.1671-6833.2013.03.027

Abstract:: In view of the difficulty in establishing precise nonlinear water quality forecast model using the tradition-al method,the paper proposed the short-term forecast model of the water quality using the weighted support vectorregression machine based on the particle swarm optimization ( PSO-WSVR). According to the importance of thesamples are significantly different，the authors proposed the penalty coefficient for the every sample to differentweighted values and improved the standard support vector regression algorithm to avoid different samples using thesame weight,which may cause the low prediction accuracy.The parameters combinations of the weighted supportvector regression machine were adaptively optimized using particle swarm optimization algorithm, which the conver-gence rate could be sped up significantly.The water quality of crab intensive aquaculture in Yixing,Jiangsu waspredicted using PSO-WSVR model. Compared with forecasting result of the standard support vector regression andBP neural network,the forecasting result of PSO-WSVR have reliable performance, generalization ability,and highforecast precision, so it provides a new way for short -term forecasting of the water quality in intensive aquaculture.

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