Robotics & Machine Learning Daily News2024,Issue(Dec.6) :155-156.

Data from Chengdu University Provide New Insights into Machine Learning (Generat ing a 30 m Hourly Land Surface Temperatures Based on Spatial Fusion Model and Ma chine Learning Algorithm)

成都大学的数据为机器学习提供了新的见解(基于空间融合模型和Ma Chine学习算法生成每小时30米的地表温度)

Robotics & Machine Learning Daily News2024,Issue(Dec.6) :155-156.

Data from Chengdu University Provide New Insights into Machine Learning (Generat ing a 30 m Hourly Land Surface Temperatures Based on Spatial Fusion Model and Ma chine Learning Algorithm)

成都大学的数据为机器学习提供了新的见解(基于空间融合模型和Ma Chine学习算法生成每小时30米的地表温度)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑新闻-人工智能的新数据出现在一份新的报告中。根据NewsRx记者从中华人民共和国成都发回的新闻报道,研究称:“陆地上的土地,土地地表温度(LST)是了解气候变化和气候变化的重要参数地方和全球范围内的水文平衡"。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Fresh data on artificial intelligence are present ed in a new report. According to news reporting originating from Chengdu, People ’s Republic of China, by NewsRx correspondents, research stated, “Landsurface t emperature (LST) is a critical parameter for understanding climate change and ma intaininghydrological balance across local and global scales.”

Key words

Chengdu University/Chengdu/People’s Re public of China/Asia/Algorithms/Cyborgs/Emerging Technologies/Machine Learn ing

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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