Robotics & Machine Learning Daily News2024,Issue(Sep.3) :69-70.

Data from University of Florida Advance Knowledge in Machine Learning (Simulating Soil Hydrologic Dynamics Using Crop Growth and Machine Learning Models)

Robotics & Machine Learning Daily News2024,Issue(Sep.3) :69-70.

Data from University of Florida Advance Knowledge in Machine Learning (Simulating Soil Hydrologic Dynamics Using Crop Growth and Machine Learning Models)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news originatingfrom Homestead, Florida, by NewsRx correspondents, research stated, “Accurate measurement of cropevapotranspirati on (ETc) and soil moisture content (SMC) is critical for different purposes, inc ludingdeveloping irrigation scheduling practices that improve water use efficie ncy and crop yield. The objectivesof this study were to 1) simulate daily ETc a nd SMC of green beans and sweet corn under full irrigationand three deficit irr igation rates using the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Green bean and CERES-Sweet corn models and 2) evaluate the performan ce of threemachine learning models for simulating ETc of green beans and sweet corn.”

Key words

Homestead/Florida/United States/North and Central America/Cyborgs/Emerging Technologies/Machine Learning/Universi ty of Florida

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文