Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)

<Previous Article In Volume
Next Article In Volume>

Evaluation method of agricultural production technical efficiency based on Borderline-SMOTE and LightGBM

Authors
Jianying Feng1, Yan Shi1, Yunhui Su1, Weisong Mu1, Dong Tian1, *
1College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China
*Corresponding author. Email: td_tiandong@cau.edu.cn
Corresponding Author
Dong Tian
Available Online 9 October 2023.
DOI
10.2991/978-94-6463-262-0_60How to use a DOI?
Keywords
technical efficiency; oversampling; regression prediction; efficiency prediction; algorithm fusion
Abstract

Data envelopment analysis (DEA) model is widely used to calculate the technical efficiency of agricultural production, but it is facing the defects of poor flexibility and slower speed. For this reason, we propose an evaluation method of agricultural production technical efficiency that integrates the DEA model, Borderline-SMOTE oversampling algorithm, and Light Gradient Boosting Machine (LightGBM) regression algorithm, and verify the effect of the method on the grape farmer dataset. The experimental results show that the MAE, MSE, and R2 of the fusion model are 4.05E-02, 5.25E-03, and 0.898 respectively on the test set when the imbalanced ratio of the dataset is 4, which is better than other comparison models under the same imbalanced ratio and other fusion models under different imbalanced ratio. It indicates that the regression model of agricultural production technical efficiency based on the Borderline-SMOTE and LightGBM algorithm has superior prediction effect and can effectively make up for the limitations of the DEA model.

Copyright
© 2024 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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
Series
Atlantis Highlights in Engineering
Publication Date
9 October 2023
ISBN
978-94-6463-262-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-262-0_60How to use a DOI?
Copyright
© 2024 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  - Jianying Feng
AU  - Yan Shi
AU  - Yunhui Su
AU  - Weisong Mu
AU  - Dong Tian
PY  - 2023
DA  - 2023/10/09
TI  - Evaluation method of agricultural production technical efficiency based on Borderline-SMOTE and LightGBM
BT  - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023)
PB  - Atlantis Press
SP  - 586
EP  - 592
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-262-0_60
DO  - 10.2991/978-94-6463-262-0_60
ID  - Feng2023
ER  -