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MLP neural network-based regional logistics demand prediction

  • S.I. : SPIoT 2020
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Abstract

The introduction of logistics theory and logistics technology has made the government and enterprises gradually realize that the development of logistics has an important strategic role, which can effectively solve the changing needs of users, optimize resource allocation, improve the investment environment, and enhance the overall strength and overall competitiveness of the regional economy. This paper carries out matrix–vector multiplication operations and weight update operations, designs a perceptron neural network model, and realizes a simulation platform based on MLP neural network. Moreover, on the basis of the standard MLP neural network, this paper proposes to use the deep learning training mechanism to improve the MLP neural network, which provides effective technical support for the improvement of the prediction model. In addition, through the fusion of deep learning and MLP neural network, an MLP neural network with three hidden layers is determined. Finally, this paper builds a model based on the MLP neural network algorithm, selects the RBF kernel function as the kernel function of the model by referring to the relevant literature, and uses PSO to optimize the combination of parameters. It can be seen from the result of the evaluation index that each evaluation index is relatively small. The result shows that the prediction is accurate, and the empirical result shows the feasibility of the model to predict the demand for industrial logistics in Shanxi Province.

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Authors and Affiliations

  1. College of Biological and Agricultural Engineering, Jilin University, Changchun, 130025, China

    Hongpeng Guo, Cheng Guo, Beichun Xu, Yujie Xia & Fanhui Sun

  2. Changchun Normal University, Changchun, 130000, China

    Beichun Xu

Authors
  1. Hongpeng Guo
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  2. Cheng Guo
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  3. Beichun Xu
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  4. Yujie Xia
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  5. Fanhui Sun
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Correspondence to Yujie Xia.

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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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Guo, H., Guo, C., Xu, B. et al. MLP neural network-based regional logistics demand prediction. Neural Comput & Applic 33, 3939–3952 (2021). https://doi.org/10.1007/s00521-020-05488-0

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