首页|New Machine Learning Findings from Sichuan University Described (Prediction of Thermodynamic Stability of Actinide Compounds By Machine Learning Model)
New Machine Learning Findings from Sichuan University Described (Prediction of Thermodynamic Stability of Actinide Compounds By Machine Learning Model)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learning have been published. According to newsreporting out of Chengdu, People’s Republic of China, by NewsRx editors, research stated, “The thermodynamicphase stability plays a crucial role as it serves as a fundamental parameter governing thesynthesizability of materials and their potential for degradation under specific operating conditions. Inthis study, two machine learning (ML) models, random forest (RF) and neural network (NN), were usedto predict the thermodynamic phase stability of actinide compounds using a dataset consisting of 62204DFT-calculated en-ergies.”
ChengduPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSichuan University
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