Studies from Central China Normal University Further Understanding of Machine Learning (Evaluation of Machine Learningdynamical Hybrid Method Incorporating Remote Sensing Data for In-season Maize Yield Prediction Under Drought)

Robotics & Machine Learning Daily News2024，Issue(Jun.17) ：25-26.

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Studies from Central China Normal University Further Understanding of Machine Learning (Evaluation of Machine Learningdynamical Hybrid Method Incorporating Remote Sensing Data for In-season Maize Yield Prediction Under Drought)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsoriginating from Wuhan, People’s Repub lic of China, by NewsRx correspondents, research stated, “Effectiveyield foreca sting is a key strategy for adaptation when facing food loss to climate variabil ity. Currently,solar-induced chlorophyll fluorescence (SIF) is an emerging remo te-sensing index owing to its high relevanceto plant photosynthesis, and sensit ivity to drought.”

Key words

Wuhan/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Remote Sensing/Central China Normal University

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出版年

2024

Robotics & Machine Learning Daily News

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