Your Location:
Home >
Browse articles >
New quality productive forces of agriculture in China based on machine learning: Regional comparison, driving factors and dynamic evolution
New quality productive forces of agriculture in China based on machine learning: Regional comparison, driving factors and dynamic evolution
- “Significant progress has been made in the research of new quality productivity in Chinese agriculture. Experts have constructed a three-dimensional comprehensive evaluation system of "laborers labor materials labor objects", integrating entropy method and SHAP interpretable machine learning method, revealing the synergistic mechanism of "innovation digital" dual wheel drive and green transformation, and providing solutions for differentiated policies for high-quality agricultural development.”
- Journal of China Agricultural University Vol. 31, Issue 8, Pages: 251-268(2026)
DOI: 10.11841/j.issn.1007-4333.2026.08.22
Accepted:28 January 2026
Scan QR Code
Full Text(HTML)
Figs( 10 ) Tabs( 4 )
References
Publication Info
Metrics
31
Views
20
Downloads
0
CSCD
Alert me when the article has been cited
Submit
Tools
- BibTeXDownload
- EndnoteDownload
- RefMan Download
- NoteExpressDownload
- NoteFirstDownload
Related Articles
Prediction of the rice blast in Hubei Province based on machine learning and multi-dimensional meteorological features
Screening of core genes and prediction of traditional Chinese medicine components for bovine respiratory disease based on machine learning and reverse network pharmacology
Research on new quality productive forces in agriculture: Critical thinking based on knowledge graphs
New quality productive forces in agriculture empowers the grain yield per unit area: Theoretical mechanism and empirical test
The factors affecting the behavior response of service providers in manure returning based on machine learning: Empirical evidence from the green planting-breeding cycle agriculture pilot program
Related Author
CAO Chunxia
LIU Hong
JIN Ruoheng
YUAN Qinfeng
WANG Beibei
HUANG Daye
CAI Yanrong
DING Xiaoying
Related Institution
Research Center for Green Development and Rural Revitalization, Guizhou University of Finance and Economics
School of Business Administration, Zhongnan University of Economics and Law
Hubei Biopesticide Engineering Research Center
College of Science, Inner Mongolia Agriculture University
Business School, Xinjiang Normal University


