首页|Reports Outline Machine Learning Study Findings from Beihang University (Classif ication Enhanced Machine Learning Model for Energetic Stability of Binary Compounds)
Reports Outline Machine Learning Study Findings from Beihang University (Classif ication Enhanced Machine Learning Model for Energetic Stability of Binary Compounds)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learning have been published. According to news reporting out of Beijing, People’s Re public of China, by NewsRx editors, research stated, “As contemporary computational technologies and machine learning methodologies rapidly evolve, machine learning (ML) models for predicting formation enthalpies of materials exhibited convincible numerical precision and remarkable predictive efficiency, thus establishing a solid foundation for materials thermodynamic design. Despite achieving numerically high global probability accuracy, current ML models for formation enthalpy nonetheless exhibit suboptimal local accuracy within specific physical domain, which can be attributed to the misalignment between the physical constraints of chemical bonds and the critical descriptors capturing classspecific traits.”
BeijingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningBeihang University
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