首页|Researcher from ShanghaiTech University Details Findings in Machine Learning (He at diffusion coefficient study of polymers based on interpretable machine learni ng)
Researcher from ShanghaiTech University Details Findings in Machine Learning (He at diffusion coefficient study of polymers based on interpretable machine learni ng)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on artificial intelligence are presented in a new report. According to newsreporting from Shanghai, People ’s Republic of China, by NewsRx journalists, research stated, “Abstract.”The news journalists obtained a quote from the research from ShanghaiTech Univer sity: “Polymershold significant application value across various fields of mode rn society, with different application scenariosrequiring specific thermal diff usivity coefficients. Finding polymer materials with targeted thermal diffusivities is crucial. However, due to the vast variety and complex structures of polym ers, constructing a unifiedstructured dataset for machine learning modeling is challenging. Although machine learning has showngreat potential in materials sc ience, it has rarely been applied to predict the heat diffusion coefficient ofp olymers. This paper constructs a dataset for predicting the thermal diffusion co efficient of polymersusing a publicly available dataset by transforming the SMI LES code of polymers into eight features withpractical physical and chemical me anings. Using the Random Forest algorithm, training with 400 of thesedata and r andomly selecting 200 of them for cross-validation, the accuracy of the test set reached 0.9.”
ShanghaiTech UniversityShanghaiPeopl e’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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