Water Quality Prediction Based on Grey-Support Vector Regression

Abstract:

Water quality prediction has a great significance to evalute the quality development trend of water and make the planning of water processing. In the study, a novel hybrid method of grey model and support vector regression is proposed to improve the prediction accuracy of sypport vector regression. COD is the important composition in the polluting water. Thus, COD is used as evaluation index of polluting water in the paper. The quality prediction values of input and output water of BP nerual network and the hybrid method of grey model and support vector regression are computated respectively. It is indicated that the water quality prediction by using the hybrid method of grey model and support vector regression is superior to BP nerual network.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 263-267
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.263
• Online since: January 2012
• Authors: Jing Du, Tao Tao
• Keywords: Gray Theory, Prediction Technique, Support Vector Regression (SVR), Water Quality

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