Forecasting Model Based on SAGA and LS-SVM for the Water Quality of Poyang Lake
Qun Cao, Bing Xiang Liu, Xiang Chen · Advanced materials research · 2011
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.