Robotics & Machine Learning Daily News2024,Issue(Aug.7) :24-25.

Reports from Federal University Goias Add New Data to Findings in Machine Learni ng (Can Machine Learning Efficiently Predict Symmetry Breaking In Physical Probl ems Like Bose-einstein Condensates?)

Robotics & Machine Learning Daily News2024,Issue(Aug.7) :24-25.

Reports from Federal University Goias Add New Data to Findings in Machine Learni ng (Can Machine Learning Efficiently Predict Symmetry Breaking In Physical Probl ems Like Bose-einstein Condensates?)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators discuss new findings in Machine Lea rning. According to news originating fromGoiania, Brazil, by NewsRx corresponde nts, research stated, “In this work, our objective is to evaluatewhether machin e learning algorithms combined with computational methods used in physical probl emssuch as spontaneous symmetry breaking in Bose-Einstein condensates are capab le of efficiently predictingresults obtained from solutions of nonlinear equati ons.”

Key words

Goiania/Brazil/South America/Algorith ms/Bose-einstein/Cyborgs/Emerging Technologies/Machine Learning/Physics/Fe deral University Goias

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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