Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model-Reference-Cited by-同舟云学术

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Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model

Published:2020-11-11 Issue:24 Volume:59 Page:7423-7440
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Jiang Peng¹²^ORCID,Huang Yibin¹,Liu Xiao³

Affiliation:

1. Department of Industrial Engineering & Management, Shanghai Jiao Tong University, Shanghai, People’s Republic of China

2. Department of Systems Science, Institute of High Performance Computing, A*STAR, Singapore

3. China Institute for Urban Governance, Shanghai Jiao tong University, Shanghai, People’s Republic of China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1842936

Reference54 articles.

1. A new method to forecast intermittent demand in the presence of inventory obsolescence

2. Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice

3. Support Vector Machine for Demand Forecasting of Canadian Armed Forces Spare Parts

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combining probabilistic forecasts of intermittent demand;European Journal of Operational Research;2024-06

2. Forecasting spare part extractions from returned systems in a closed-loop supply chain;International Journal of Production Research;2024-03-30

3. Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering;Journal of Forecasting;2024-02-28

4. A hybrid LSTM method for forecasting demands of medical items in humanitarian operations;International Journal of Production Research;2024-02-13

5. Maintenance Spare Parts Prediction Based on Multilevel Migration Learning CNN-ISE-Attention-BiLSTM;IEEE Access;2024

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