首页|Tianjin University Reports Findings in Machine Learning [Pred iction and Interpretability Study of the Glass Transition Temperature of Polyimi de Based on Machine Learning with Quantitative Structure- Property Relationship ( Tg-QSPR)]
Tianjin University Reports Findings in Machine Learning [Pred iction and Interpretability Study of the Glass Transition Temperature of Polyimi de Based on Machine Learning with Quantitative Structure- Property Relationship ( Tg-QSPR)]
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsreporting from Tianjin, People’s Republ ic of China, by NewsRx journalists, research stated, “The glasstransition tempe rature () is a crucial characteristic of polyimides (PIs). Developing a predicti ve model usingmachine learning methodologies can facilitate the design of PI st ructures and expedite the developmentprocess.”
TianjinPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine Learning
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