Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)

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Research on Relevant Factors of Helping Rural Revitalization Based on Machine Learning Analysis - Taking Kengwei Village in Shantou City as an Example

Authors
Chun Zhou1, Yisi Chen2, Jingyi Zhao1, Changzhi Niu1, Mengyao Wang1, *, Xin Ma3, Ying Feng2, Yi Zhang2
1Big Data College, Zhuhai College of Science and Technology, Zhuhai, China, 519000
2School of Internet Finance and Information Engineering, Guangdong University of Finance, Guangzhou, China, 510000
3School of Pharmaceutical Business, Guangdong Pharmaceutical University, Zhongshan, China, 528400
*Corresponding author. Email: wangmengyao_o@qq.com
Corresponding Author
Mengyao Wang
Available Online 22 November 2024.
DOI
10.2991/978-94-6463-570-6_146How to use a DOI?
Keywords
data analysis; rural revitalization; decision tree; K-nearest neighbour (KNN); logistic regression
Abstract

Nowadays, the development of rural areas still faces difficulties and challenges, such as unbalanced economic development, insufficient infrastructure and public services, and backwardness of education level due to brain drain still exist. In order to promote the modernization of agriculture and industrial upgrading, and to support the sustainable development of the national economy, the article takes Kengwei Village in Shantou City as an example, and carries out a specific analysis of the factors that promote the revitalization of the countryside based on the relevant application of machine learning using the algorithms of K-nearest neighbour (KNN), decision tree, logistic regression, and random forest. Through data visualization, a more intuitive understanding of the cognitive village, enhance the understanding of the three rural issues, and actively contribute to rural revitalization.

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.

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Volume Title
Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
22 November 2024
ISBN
978-94-6463-570-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-570-6_146How 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  - Chun Zhou
AU  - Yisi Chen
AU  - Jingyi Zhao
AU  - Changzhi Niu
AU  - Mengyao Wang
AU  - Xin Ma
AU  - Ying Feng
AU  - Yi Zhang
PY  - 2024
DA  - 2024/11/22
TI  - Research on Relevant Factors of Helping Rural Revitalization Based on Machine Learning Analysis - Taking Kengwei Village in Shantou City as an Example
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 1445
EP  - 1456
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_146
DO  - 10.2991/978-94-6463-570-6_146
ID  - Zhou2024
ER  -