Prediction and Industrial Structure Analysis of Local GDP Economy Based on Machine Learning

Author:

Jiang Zhiqiang1ORCID

Affiliation:

1. School of Business, Huaiyin Institute of Technology, Huaian 223001, China

Abstract

The process of regional economic growth is a long-term evolutionary law. During this long evolutionary process, some regions may continue to grow, while others may fall into decline. It takes a long time. For example, from the perspective of our country’s regional economic growth since the turn of the century, the east coast has been in a relatively developed state, while the economy of some western regions is relatively backward. Therefore, how to promote the long-term growth of developed regions and revitalize the troubled regional economy by studying the long-term growth mechanism of the regional economy is an important topic of regional economic research. In this context, we can draw the following conclusions. (1) The employment structure of major industries has been declining year by year since 2000, and this trend is relatively obvious and the decline is relatively large. Despite some changes in industrial growth, the overall trend is upward. The employment structure of the service industry has increased year by year, and its proportion in total employment usually exceeds that of major industries, and it is the industry with the largest number of employees. (2) The accuracy under the machine learning model is 79.46%, the reliability is 89.27%, and it is feasible; the accuracy under the data mining model is 68.45%, the reliability is 75.43%, and the feasibility is 86.18%; the accuracy rate under the traditional statistical model is 60.14%, the feasibility is 68.24%, and the reliability is 75.12%. GDP not only is the core indicator of national economic accounting but also can be used to measure the economic status and development level of a country or region. The impact of industrial structure on GDP is huge, and a suitable industrial structure can promote a healthier growth of GDP. In order to analyze the relationship between our country’s GDP and industrial structure, the quantitative analysis method of grey correlation analysis is used to study it, and then according to the calculation results, suggestions for adjusting and optimizing the industrial structure will be put forward to the relevant ministries.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Cited by 4 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. Exploring Global Economy Evolution: Clusters and Patterns;Economies;2024-01-29

2. GDP Prediction Model of Guangdong Province based on Pearson Correlation Coefficient Analysis;International Conference on Mathematics and Machine Learning;2023-11-24

3. Ham2Pose: Animating Sign Language Notation into Pose Sequences;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06

4. Huizhou GDP forecast based on fractional opposite-direction accumulating nonlinear grey bernoulli markov model;Electronic Research Archive;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3