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In the study, support vector machine trained with genetic algorithm is applied in GDP forecasting. Genetic algorithm can get optimal solution in short time, which is an excellent method in parameters selection of support vector machine. Then, genetic algorithm is introduced to simultaneously optimize the SVM parameters. The total GDP data of Anhui province from 1989 to 2007 are employed to compare...
The support vector machine (SVM), proposed by Vapnik (1995), has been successfully applied to classification, cluster, and forecast. This study proposes support vector regression (SVR) to forecast real estate prices in China. The aim of this paper is to examine the feasibility of SVR in real estate price prediction. To achieve the aim, five indicators are selected as the input variables and real estate...
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