The Research on Forecasting Model Based on Support Vector Machine and Discrete Grey System

Chengli Zhao, Zhiheng Yu
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引用次数: 1

Abstract

In order to improve the prediction accuracy, this paper proposes a combined forecasting model based on the residual correction of DGM (1,1). After introducing the basic DGM(1,1) model and LSSVM regression model, DGM-LSSVM combination model is established. In this model, DGM(1, 1) is used to predict the original data sequence and obtain the predictive value and residual value. Then LSSVM model is used to correct the residual errors. Finally, the predicted results of DGM (1, 1) and residual correction of LSSVM model are combined, and the final prediction result is obtained by the combination forecasting model. Experimental results demonstrate that the proposed model has the advantages of effectiveness and feasibility.
基于支持向量机和离散灰色系统的预测模型研究
为了提高预测精度,本文提出了一种基于DGM(1,1)残差校正的组合预测模型。在引入基本的DGM(1,1)模型和LSSVM回归模型后,建立了DGM-LSSVM组合模型。在该模型中,利用DGM(1,1)对原始数据序列进行预测,得到预测值和残值。然后利用LSSVM模型对残差进行校正。最后,将DGM(1,1)的预测结果与LSSVM模型的残差校正相结合,通过组合预测模型得到最终的预测结果。实验结果表明,该模型具有有效性和可行性。
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