Robotics & Machine Learning Daily News2024,Issue(Oct.10) :111-111.

Sanming University Reports Findings in Machine Learning (Quantification of uncer tainty in short-term tropospheric column density risks for a wide range of carbo n monoxide)

Robotics & Machine Learning Daily News2024,Issue(Oct.10) :111-111.

Sanming University Reports Findings in Machine Learning (Quantification of uncer tainty in short-term tropospheric column density risks for a wide range of carbo n monoxide)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Sanming, Peopl e’s Republic of China, by NewsRx journalists, research stated, “The short-term r isks associated with atmospheric trace gases, particularly carbon monoxide (CO), are critical for ecological security and human health. Traditional statistical methods, which still dominate the assessment of these risks, limit the potential for enhanced accuracy and reliability.”

Key words

Sanming/People’s Republic of China/Ani ons/COVID-19 Model/Carbon Monoxide/Chemicals/Cyborgs/Disease Model/Emergin g Technologies/Epidemiology/Inorganic Carbon Compounds/Machine Learning/Oxid es/Risk and Prevention

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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