Supply Chain Demand Forecasting Based on WOA-ELM

DOI

10.2991/978-94-6463-030-5_131How to use a DOI?

Keywords

Supply Chain Management; Supply Chain Demand; WOA-ELM; Hybrid Model

Abstract

In the whole supply chain management process, accurate control of supply chain demand is an important part. In order to study supply chain demand with predictability and credibility, an extreme learning machine model based on whale optimization algorithm is proposed. By analyzing the demand of a company for 14 months, the data relationship is constructed from seven influencing factors including cost, seasonal coefficient, sales intensity, market characteristics, number of shoppers, product structure and credit index. After the training of WOA-ELM model data, the average error result is 5.71%, which has a good error effect. It can provide a new idea for supply chain demand forecasting.

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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TY  - CONF
AU  - Lijie Zhao
PY  - 2022
DA  - 2022/12/20
TI  - Supply Chain Demand Forecasting Based on WOA-ELM
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 1315
EP  - 1324
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_131
DO  - 10.2991/978-94-6463-030-5_131
ID  - Zhao2022
ER  -