Robotics & Machine Learning Daily News2024,Issue(MAY.16) :22-23.

New Machine Learning Study Results Reported from Tomsk Polytechnic University (R obust Machine Learning Predictive Models for Real-time Determination of Confined Compressive Strength of Rock Using Mudlogging Data)

Robotics & Machine Learning Daily News2024,Issue(MAY.16) :22-23.

New Machine Learning Study Results Reported from Tomsk Polytechnic University (R obust Machine Learning Predictive Models for Real-time Determination of Confined Compressive Strength of Rock Using Mudlogging Data)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Tomsk, Russia, by NewsRx edit ors, research stated, “Mud logging data, which quantify the energy expended in r ock breaking during drilling, are routinely acquired during drilling. These data offer a practical means to estimate the geomechanical properties of rocks, part icularly confined compressive strength (CCS), avoiding the need for costly and d estructive laboratory tests.”

Key words

Tomsk/Russia/Cyborgs/Emerging Technol ogies/Machine Learning/Tomsk Polytechnic University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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