计算机应用 ›› 2017, Vol. 37 ›› Issue (4): 1038-1043.DOI: 10.11772/j.issn.1001-9081.2017.04.1038

• 数据科学与技术 • 上一篇    下一篇

基于跨境电商可控关联性大数据的出口产品销量动态预测模型

王雪蓉, 万年红   

  1. 浙江东方职业技术学院 信息传媒与自动化学院, 浙江 温州 325011
  • 收稿日期:2016-07-29 修回日期:2016-10-20 出版日期:2017-04-10 发布日期:2017-04-19
  • 通讯作者: 万年红
  • 作者简介:王雪蓉(1981-),女,浙江平阳人,副教授,硕士,主要研究方向:跨境电商、大数据;万年红(1977-),男,江西南昌人,副教授,硕士,主要研究方向:互联网+、大数据、跨境电商。
  • 基金资助:
    浙江省社会科学界联合会研究课题成果(2017Z03)。

Dynamic prediction model on export sales based on controllable relevance big data of cross-border e-commerce

WANG Xuerong, WAN Nianhong   

  1. School of Information Media and Automation, Zhejiang Dongfang Vocational and Technical College, Wenzhou Zhejiang 325011, China
  • Received:2016-07-29 Revised:2016-10-20 Online:2017-04-10 Published:2017-04-19
  • Supported by:
    This paper is supported by Research Projects of Zhejiang Federation of Humanities and Social Sciences Circles (2017Z03).

摘要: 目前流行的外贸产品销量预测方法单纯地分别从第三方平台或大数据角度研究预测问题,对互联网平台、跨境电商、大数据融合应用于产品销量动态演化预测的考虑不足。为提高出口产品销量预测效果,实现预测系统的伸缩性和动态演化性,基于研究"互联网+外贸"环境下跨境电商出口产品销量可控关联性大数据挖掘、个性化预测机制、智慧预测算法,改进分布式定量、集中式定性计算等相应算法,提出一个"互联网+外贸"驱动下基于跨境电商可控关联性大数据的出口产品销量动态预测模型,并进行了应用实验,对各种模型的实验结果进行对比分析。实验结果表明,该模型充分融合了"互联网+"的开放性、可延伸性和大数据动态预测优势,实现了"互联网+外贸"环境下基于跨境电商可控关联性大数据的出口产品销量动态、智慧、定量定性预测。该模型综合预测效果明显优于传统模型,具有较强的动态演化性和较高的实用价值。

关键词: 互联网+外贸, 跨境电商, 可控关联性大数据, 出口产品销量, 动态预测

Abstract: Current popular prediction methods of foreign trade product sales only respectively study prediction problems from angles of the third party platform or big data, lacking consideration of dynamic evolution prediction on product sales based on Internet platform, big data and cross-border e-commerce. To improve the efficiency of export sales prediction, to achieve scalability and dynamic evolution of prediction systems, with mining controllable relevance big data of cross-border e-commerce export sale based on "Internet+foreign trade" surroundings, personalized prediction mechanism and smart prediction algorithms, improving corresponding algorithms such as distributed quantitative calculation and centralized qualitative calculation, a dynamic prediction model on export sales based on "Internet+foreign trade"-driven controllable relevance big data of cross-border e-commerce was proposed. Finally, this model was verified and analyzed. The performance analysis results show that the model integrates fully openness and extensibility of "Internet+" and dynamic prediction advantages of big data, achieving dynamic, smart, quantitative, and qualitative prediction on export sales based on "Internet+foreign trade"-driven controllable relevance big data of cross-border e-commerce. The comprehensive prediction efficiency of the proposed model is obviously better than those of traditional models, and it has stronger dynamic evolution and higher utility.

Key words: Internet+foreign trade, cross-border e-commerce, controllable relevance big data, export sale number, dynamic prediction

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