Robotics & Machine Learning Daily News2024,Issue(Dec.26) :18-18.

Researchers at Chinese Academy of Sciences Release New Data on Machine Learning (A Gsd-driven Approach To Deriving Stochastic Soil Strength Parameters Under Hyb rid Machine Learning Models)

Robotics & Machine Learning Daily News2024,Issue(Dec.26) :18-18.

Researchers at Chinese Academy of Sciences Release New Data on Machine Learning (A Gsd-driven Approach To Deriving Stochastic Soil Strength Parameters Under Hyb rid Machine Learning Models)

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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 reportingoriginating in Chengdu, People’s Rep ublic of China, by NewsRx journalists, research stated, “The quantificationof s oil strength parameters is a crucial prerequisite for constructing physical mode ls relatedto hydro-geophysical processes. However, due to ignoring soil spatial variability at different scales, traditionalparameter assignment strategies, s uch as assigning values depending on land use classification orother classifica tion systems, as well as those extrapolation and interpolation methods, are insu fficient forphysical process modelling.”

Key words

Chengdu/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Perceptron/Chinese Academy of Sciences

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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