首页|New Machine Learning Research from Pusan National University Outlined (Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation)
New Machine Learning Research from Pusan National University Outlined (Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting originating from Busan, South Kor ea, by NewsRx correspondents, research stated, "Mg alloys possess an inherent pl astic anisotropy owing to the selective activation of deformation mechanisms dep ending on the loading condition." Our news journalists obtained a quote from the research from Pusan National Univ ersity: "This characteristic results in a diverse range of flow curves that vary with a deformation condition. This study proposes a novel approach for accurate ly predicting an anisotropic deformation behavior of wrought Mg alloys using mac hine learning (ML) with data augmentation. The developed model combines four key strategies from data science: learning the entire flow curves, generative adver sarial networks (GAN), algorithm-driven hyperparameter tuning, and gated recurre nt unit (GRU) architecture. The proposed model, namely GANaided GRU, was extens ively evaluated for various predictive scenarios, such as interpolation, extrapo lation, and a limited dataset size. The model exhibited significant predictabili ty and improved generalizability for estimating the anisotropic compressive beha vior of ZK60 Mg alloys under 11 annealing conditions and for three loading direc tions. The GAN-aided GRU results were superior to those of previous ML models an d constitutive equations."
Pusan National UniversityBusanSouth KoreaAsiaAlloysCyborgsEmerging TechnologiesMachine Learning
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