Data Analysis of Major Industries in the Country Based on Economic Indicators and Machine Learning Technology

DOI

10.2991/978-94-6463-010-7_70How to use a DOI?

Keywords

Main Industries; Developing Country; Developed Country; Normalization; Correlation; Decision-Tree; Chi-Square Test; Policies

Abstract

In this article, we tend to prove whether some economic indicators related to the three industries are characteristics of the development status of each country. Therefore, we first classify each country into developed, moderately developed, and developing based on per capita GDP. After that, we conducted surveys on 42 countries based on three industrial indicators: the employment rate of the primary industry, the employment rate of the secondary industry, the employment rate of the tertiary industry, the proportion of agricultural added value in GDP, the proportion of industrial added value in GDP, and the proportion of industrial added value. Classification. The added value of the service industry accounts for GDP and agricultural production index. Based on these data, we standardize to avoid bias due to different measurements of these variables. Then, apply correlation analysis to eliminate some variables. Next, hierarchical clustering and decision trees help us find the criteria for classifying these countries into three categories. After obtaining the category, we matched the classification result with the category derived from GDP per capita, and successfully verified our hypothesis through the chi-square test. Finally, we put forward some suggestions for the development of moderately developed countries and developing countries based on our research results.

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.

Download article (PDF)

TY  - CONF
AU  - Yinzhou Xiao
AU  - Meili Liu
AU  - Chun-Te Lee
AU  - Jeng-Eng Lin
PY  - 2022
DA  - 2022/12/02
TI  - Data Analysis of Major Industries in the Country Based on Economic Indicators and Machine Learning Technology
BT  - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
PB  - Atlantis Press
SP  - 679
EP  - 693
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-010-7_70
DO  - 10.2991/978-94-6463-010-7_70
ID  - Xiao2022
ER  -