Study on logistics demand forecasting model based on fuzzy cognitive map

HAN Huijian, HAN Jiabing, ZHANG Rui

Systems Engineering - Theory & Practice ›› 2019, Vol. 39 ›› Issue (6) : 1487-1495.

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Systems Engineering - Theory & Practice ›› 2019, Vol. 39 ›› Issue (6) : 1487-1495. DOI: 10.12011/1000-6788-2018-0712-09

Study on logistics demand forecasting model based on fuzzy cognitive map

  • HAN Huijian, HAN Jiabing, ZHANG Rui
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Abstract

Accurate prediction of social logistics demands is essential to government's policy formulation for the logistics industry as well as to enterprise's logistics activity planning. In this paper, a logistics demand prediction model construction method based on the fuzzy cognitive map (FCM) is proposed. This method comprehensively considers the mutual influence between five economic elements (GDP, total import and export volume, etc.) and logistics demands, and acquires the mutual influence weight through machine learning of historical data. Finally, a logistics demand prediction model is built, which can realize accurate prediction of the future logistics demands. The experimental results provide solid evidence for high precision and favorable performance of the model in predicting logistics demands.

Key words

logistics demand / machine learning / fuzzy cognitive map

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HAN Huijian , HAN Jiabing , ZHANG Rui. Study on logistics demand forecasting model based on fuzzy cognitive map. Systems Engineering - Theory & Practice, 2019, 39(6): 1487-1495 https://doi.org/10.12011/1000-6788-2018-0712-09

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Funding

National Social Science Foundation of China (18BJL047); Key Project of Social Science Planning of Shandong Province of China (18BGLJ05); Humanities and Social Sciences Foundation of Ministry of Education of China (14YJC860011)
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