首页|Reports Outline Machine Learning Study Results from Guizhou Normal University (I dentifying Key Features for Predicting Glassforming Ability of Bulk Metallic Gl asses Via Interpretable Machine Learning)
Reports Outline Machine Learning Study Results from Guizhou Normal University (I dentifying Key Features for Predicting Glassforming Ability of Bulk Metallic Gl asses Via Interpretable Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting from Guiyang, People’ s Republic of China, by NewsRx journalists, research stated, “Bulk metallic glas ses (BMGs) have been receiving extensive attention in the community of physics a nd materials science due to their attractive properties. The traditional trial-a nd-error approach is inefficient in designing good BMGs, then it is imperative t o elaborate a prediction scheme to accelerate the development of BGMs.” Financial supporters for this research include National Key R&D Pro gram of China, National Natural Science Foundation of China (NSFC).
GuiyangPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningGuizhou Normal University
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