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首页> 外文期刊>Mathematical Problems in Engineering >An Application of a Three-Stage XGBoost-Based Model to Sales Forecasting of a Cross-Border E-Commerce Enterprise
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An Application of a Three-Stage XGBoost-Based Model to Sales Forecasting of a Cross-Border E-Commerce Enterprise

机译：基于三阶段的基于XGBoost的模型在跨境电子商务企业销售预测中的应用

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摘要

Sales forecasting is even more vital for supply chain management in e-commerce with a huge amount of transaction data generated every minute. In order to enhance the logistics service experience of customers and optimize inventory management, e-commerce enterprises focus more on improving the accuracy of sales prediction with machine learning algorithms. In this study, a C-A-XGBoost forecasting model is proposed taking sales features of commodities and tendency of data series into account, based on the XGBoost model. A C-XGBoost model is first established to forecast for each cluster of the resulting clusters based on two-step clustering algorithm, incorporating sales features into the C-XGBoost model as influencing factors of forecasting. Secondly, an A-XGBoost model is used to forecast the tendency with the ARIMA model for the linear part and the XGBoost model for the nonlinear part. The final results are summed by assigning weights to forecasting results of the C-XGBoost and A-XGBoost models. By comparison with the ARIMA, XGBoost, C-XGBoost, and A-XGBoost models using data from Jollychic cross-border e-commerce platform, the C-A-XGBoost is proved to outperform than other four models.
机译：销售预测对于电子商务中的供应链管理更为重要，每分钟产生大量的交易数据。为了提高客户的物流服务经验，优化库存管理，电子商务企业更多地关注提高机器学习算法销售预测的准确性。在本研究中，基于XGBoost模型，提出了C-A-XGBoost预测模型的销售商品的销售特征和数据序列的趋势。首先建立一个C-XGBoost模型以基于两步聚类算法的所得集群的每个集群的预测，将销售特征与C-XGBoost模型结合到C-XGBoost模型中的影响因素。其次，使用A-XGBoost模型来预测非线性部件的线性部分和XGBoost模型的Arima模型的趋势。通过将权重分配给C-XGBoost和A-XGBoost模型的结果来概括最终结果。通过与ARIMA，XGBoost，C-XGBoost和A-XGBoost模型的比较，使用来自Jollychic跨界电子商务平台的数据，证明C-A-XGBoost比其他四种模型优于差不多。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第19期|8503252.1-8503252.15|共15页
  • 作者

    Ji Shouwen; Wang Xiaojing; Zhao Wenpeng; Guo Dong;

  • 作者单位

    Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China;

    Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China;

    Beijing Capital Int Airport Co Ltd Beijing 100621 Peoples R China;

    Beijing Univ Civil Engn & Architecture Sch Mech Elect & Vehicle Engn Beijing 102600 Peoples R China;

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