首页|National Yang Ming Chiao Tung University Researchers Describe Recent Advances in Machine Learning (Predictions of Lattice Parameters in NiTi High-Entropy Shape- Memory Alloys Using Different Machine Learning Models)
National Yang Ming Chiao Tung University Researchers Describe Recent Advances in Machine Learning (Predictions of Lattice Parameters in NiTi High-Entropy Shape- Memory Alloys Using Different Machine Learning Models)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on artificial intelligence have been presented. According to news originating from Hsinchu, Taiwan, by NewsRx correspondents, research stated, “This work applied three machine learning (ML) models-linear regression (LR), random forest (RF), and support vector regression (SVR)-to predict the lattice parameters of the monoclinic B19’ phase in two distinct training datasets: previously published ZrO -based shape-memory ceramics (SMCs) And NiTi-based high-entropy shape-memory alloys (HESMAs).”
National Yang Ming Chiao Tung UniversityHsinchuTaiwanAsiaAlloysCyborgsEmerging TechnologiesMachine Learning
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