首页|Studies from Xi’an Jiaotong University in the Area of Machine Learning Reported (Accurate Prediction of Magnetocaloric Effect In Nimn-based Heusler Alloys By Pr ioritizing Phase Transitions Through Explainable Machine Learning)
Studies from Xi’an Jiaotong University in the Area of Machine Learning Reported (Accurate Prediction of Magnetocaloric Effect In Nimn-based Heusler Alloys By Pr ioritizing Phase Transitions Through Explainable Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators discuss new findings in Machine Learning. According to news reporting out of Xi’an, People’s Republic of China, by NewsRx editors, research stated, “With the rapid development of artif icial intelligence, magnetocaloric materials as well as other materials are bein g developed with increased efficiency and enhanced performance. However, most st udies do not take phase transitions into account, and as a result, the predictio ns are usually not accurate enough.”
Xi’anPeople’s Republic of ChinaAsiaAlloysCyborgsEmerging TechnologiesMachine LearningXi’an Jiaotong Univer sity
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