Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology (ECIT 2022)

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Research on Dynamic Prediction Model of Orders in E-Commerce Distribution Center for Intelligent Scheduling

Authors
Yu Wang1, Zhuan Wang1, *
1School of College of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China
*Corresponding author. Email: wangzhuan@ustb.edu.cn
Corresponding Author
Zhuan Wang
Available Online 10 November 2022.
DOI
10.2991/978-94-6463-005-3_25How to use a DOI?
Keywords
Order predict; BP neural network; Genetic algorithm; Intelligent scheduling
Abstract

Based on the intelligent development and order production of e-commerce distribution center, intelligent scheduling of e-commerce distribution center is imperative. A dynamic prediction model based on BP neural network is proposed, which can quantitatively predict the order quantity between scheduling time and the cut-off time of the current wave, so as to support the decision-making of scheduling mode and scheduling batch. Firstly, a time-series structure model of order quantity with minute as time granularity was established. The time step and statistical time period were used to calculate the input parameters of neural network, and the prediction time range was taken as the output parameters of the neural network. The prediction model was obtained through multiple training, and the corresponding network model of the required prediction period was called to achieve the dynamic prediction target; Secondly, GA (Genetic Algorithm) was used to optimize the weights and threshold values of BP neural network; Finally, taking the daily order data of a pharmaceutical e-commerce distribution center as an example, the prediction model was verified. The result shows that the BP neural network model optimized by GA has better prediction effect, and the accuracy of the model meets the requirement.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology (ECIT 2022)
Series
Atlantis Highlights in Engineering
Publication Date
10 November 2022
ISBN
10.2991/978-94-6463-005-3_25
ISSN
2589-4943
DOI
10.2991/978-94-6463-005-3_25How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yu Wang
AU  - Zhuan Wang
PY  - 2022
DA  - 2022/11/10
TI  - Research on Dynamic Prediction Model of Orders in E-Commerce Distribution Center for Intelligent Scheduling
BT  - Proceedings of the 2022 3rd International Conference on E-commerce and Internet Technology (ECIT 2022)
PB  - Atlantis Press
SP  - 248
EP  - 260
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-005-3_25
DO  - 10.2991/978-94-6463-005-3_25
ID  - Wang2022
ER  -