Robotics & Machine Learning Daily News2024,Issue(Nov.6) :37-37.

Findings from National Institute of Technology Update Knowledge of Machine Learn ing (Temperature-dependent Magnetic Properties of Bcc and Fcc Feni Alloys: a Mac hine Learning Assisted Montecarlo Approach)

Robotics & Machine Learning Daily News2024,Issue(Nov.6) :37-37.

Findings from National Institute of Technology Update Knowledge of Machine Learn ing (Temperature-dependent Magnetic Properties of Bcc and Fcc Feni Alloys: a Mac hine Learning Assisted Montecarlo Approach)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented.According to news reporting from Tamil Nadu, India, by NewsRx j ournalists, research stated, “The estimation of exchange integrals in metals and alloys from first-principle calculations yields Curie temperature (TC), which i s not in agreement with the experiments.The microscopic exchange interactions o f the bcc and fcc FeNi alloys are predicted by training large datasets of random magnetization curves simulated using the atomic scale Monte Carlo method with r egression models to accurately reproduce the experimental TC.”

Key words

Tamil Nadu/India/Asia/Alloys/Cyborgs/Emerging Technologies/Machine Learning/National Institute of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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