Proceedings of the 2026 5th International Conference on Engineering Management and Information Science (EMIS 2026)

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Machine Learning-Based Classification-Regression Model for Home Appliance Logistics Delivery Time Prediction

Authors
Yixuan Sun1, Xin Wang1, *, Yi Li1
1Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
*Corresponding author. Email: s242431019@stu.cqupt.edu.cn
Corresponding Author
Xin Wang
Available Online 19 April 2026.
DOI
10.2991/978-94-6239-652-4_8How to use a DOI?
Keywords
Home Appliance Logistics; Classification-Regression; Delivery Time Prediction; Machine Learning
Abstract

Accurate prediction of home appliance delivery time is crucial for enhancing customer satisfaction, yet existing research fails to account for appliance characteristics and ignores variations in delivery time windows. Based on 3.491 million home appliance delivery samples from Ririshun Logistics, this study employs cumulative interval experiments to identify ≤ 96 h as the core prediction interval. A two-stage classification-regression model is designed (first assigning five labels, then customizing a regression model). Experiments demonstrate that compared to a single regression model, this approach reduces Root Mean Square Error (RMSE) by 6.4% and Mean Absolute Error (MAE) by 25.2%, filling a gap in home appliance logistics delivery time prediction and supporting scenario-specific operations.

Copyright
© 2026 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 2026 5th International Conference on Engineering Management and Information Science (EMIS 2026)
Series
Advances in Computer Science Research
Publication Date
19 April 2026
ISBN
978-94-6239-652-4
ISSN
2352-538X
DOI
10.2991/978-94-6239-652-4_8How to use a DOI?
Copyright
© 2026 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  - Yixuan Sun
AU  - Xin Wang
AU  - Yi Li
PY  - 2026
DA  - 2026/04/19
TI  - Machine Learning-Based Classification-Regression Model for Home Appliance Logistics Delivery Time Prediction
BT  - Proceedings of the  2026 5th International Conference on Engineering Management and Information Science (EMIS 2026)
PB  - Atlantis Press
SP  - 72
EP  - 80
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-652-4_8
DO  - 10.2991/978-94-6239-652-4_8
ID  - Sun2026
ER  -