首页|Recent Findings from Jiangsu University Provides New Insights into Machine Learn ing (Improving Carbon Flux Estimation In Tea Plantation Ecosystems: a Machine Le arning Ensemble Approach)
Recent Findings from Jiangsu University Provides New Insights into Machine Learn ing (Improving Carbon Flux Estimation In Tea Plantation Ecosystems: a Machine Le arning Ensemble Approach)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Investigators publish new report on Ma chine Learning. According to news reporting from Zhenjiang, People's Republic of China, by NewsRx journalists, research stated, "Tea plant (Camellia sinensis) i s a major global crop consumed as a drink after water. Quantifying carbon flux, specifically the net ecosystem exchange (NEE), in tea plantations is essential f or determining carbon sequestration and ecosystem carbon balance." Funders for this research include Key R & D Programme of the Jiang su Provincial Government, Priority Academic Programme Development of the Jiangsu Higher Education Institutions.
ZhenjiangPeople's Republic of ChinaA siaCyborgsEmerging TechnologiesMachine LearningJiangsu University
NETL
NSTL
