Forecasting Model Based on SAGA and LS-SVM for the Water Quality of Poyang Lake

Abstract:

According to the nonlinearity and uncertainty of the water quality data samples, a forecasting model based on Simulated Annealing Genetic Algorithm(SAGA)and least squares support vector machines(LS-SVM) is proposed. Through adaptively optimizing the model parameters of LS-SVM by SAGA, we can apply the model to forecast water quality of Poyang Lake. The experimental results indicate that compared to the typical LS-SVM,the model is very practical and with higher precision.

• Periodical: Advanced Materials Research (Volumes 347-353)
• Pages: 781-785
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.347-353.781
• Online since: October 2011
• Authors: Qun Cao, Bing Xiang Liu, Xiang Chen
• Keywords: Least Squares Support Vector Machines (Ls-SVM), Poyang Lake, Saga, Water Quality Prediction

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