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Supply chain management model based on machine learning

  • S.I.: Artificial Intelligence Technologies in Sports and Art Data Applications
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Abstract

The supply chain management process in the Internet of Things and the information age needs to deal with massive amounts of data and several influencing factors. Therefore, traditional supply chain management models cannot cope with the needs of modern supply chain management. Based on this, this paper combines machine learning and human–computer interaction technology to construct a supply chain management model, and uses wireless sensor networks as the basis of machine learning and human–computer interaction supply chain models. Combine human–computer interaction algorithms with smart learning algorithms, use machine learning for wireless sensor network data processing, and combine smart learning for data analysis. Moreover, this paper combines the actual needs of the supply chain model to improve the wireless sensor network so that it can meet the operational needs of the supply chain model. In addition, this paper starts with the construction of multiple module functions from the aspects of supply chain management risk, supply chain logistics, supply chain management, and supply chain information transmission. Finally, this paper designs experiments to verify the performance of the system in this paper. The experimental research results show that the supply chain management model based on machine learning and human–computer interaction constructed in this paper has good results.

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Funding

Funding was provided by Scientific Research Project of Shanghai Science (Grant No. 19511102202).

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Authors and Affiliations

  1. School of Economics and Management, Shanghai University of Political Science and Law, Shanghai, 201701, China

    Guanghui Yuan

  2. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Shan Wu

  3. School of Humanities, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Bin Wang

Authors
  1. Guanghui Yuan
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  2. Shan Wu
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  3. Bin Wang
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Corresponding author

Correspondence to Shan Wu.

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The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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Cite this article

Yuan, G., Wu, S. & Wang, B. Supply chain management model based on machine learning. Neural Comput & Applic 35, 4319–4335 (2023). https://doi.org/10.1007/s00521-022-06986-z

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  • DOI: https://doi.org/10.1007/s00521-022-06986-z

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