首页|Researchers at King Mongkut's University of Technology Thonburi (KMUTT) Release New Data on Machine Learning (Effects of Spatial Microstructure Characteristics On Mechanical Properties of Dual Phase Steel By Inverse Analysis and Machine ... )
Researchers at King Mongkut's University of Technology Thonburi (KMUTT) Release New Data on Machine Learning (Effects of Spatial Microstructure Characteristics On Mechanical Properties of Dual Phase Steel By Inverse Analysis and Machine ... )
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A new study on Machine Learning is now available. According to news reporting out of Bangkok, Thailand, by NewsRx edit ors, research stated, "This work aims to investigate complex relationship betwee n microstructure characteristics and mechanical properties of dual phase (DP) st eel through an inverse analysis based on Markov chain Monte Carlo (MCMC) method combined with meso-scale material modelling. In this framework, a machine learni ng approach as surrogate model was developed, in which support vector regression (SVR) and artificial neural network (ANN) were trained using results from repre sentative volume element (RVE) simulations coupled with damage model, which were previously calibrated with experimental data of commercial DP steel grades." Funders for this research include Petchra Pra Jom Klao Master's Degree Research Scholarship, Reserach Strengthening Project of the Faculty of Engineering from K ing Mongkut's University of Technology Thonburi, Thailand Advance Institute of S cience and Technology-Tokyo Institute of Technology (TAISTTokyo Tech), Thailand Science Research and Innovation (TSRI), National Science, Research and Innovati on Fund (NSRF), National Research Council of Thailand (NRCT).
BangkokThailandAsiaCyborgsEmergi ng TechnologiesMachine LearningKing Mongkut's University of Technology Thonb uri (KMUTT)
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