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Customer demand forecasting based on SVR using moving time window method

机译:基于移动时间窗方法的基于SVR的客户需求预测

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摘要

The principles of support vector regression (SVR) are described. The collection and treatment of customer demand, the moving time window method, the selection of training samples and the analysis of forecasting accuracy are stated. The customer demand forecasting approach based on SVR using moving time window method is proposed. With the demand data of a simulation example, the presented approach is used to forecast the demand values for 7 days ahead. The average forecasting error is less than 2%. The simulation results demonstrate the approach is feasible and valid in customer demand forecasting.
机译:描述了支持向量回归(SVR)的原理。阐述了客户需求的收集和处理,移动时间窗口方法,训练样本的选择以及预测准确性的分析。提出了一种基于SVR的移动时间窗方法的客户需求预测方法。利用模拟示例的需求数据,所提出的方法用于预测未来7天的需求值。平均预测误差小于2%。仿真结果表明该方法在客户需求预测中是可行和有效的。

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