首页|Reports Outline Machine Learning Study Results from Sichuan University (Article Exploring an Accurate Machine Learning Model To Quickly Estimate Stability of Di verse Energetic Materials)
Reports Outline Machine Learning Study Results from Sichuan University (Article Exploring an Accurate Machine Learning Model To Quickly Estimate Stability of Di verse Energetic Materials)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating from Chengdu, People’s R epublic of China, by NewsRx correspondents, research stated, “High energy and lo w sensitivity have been the focus of developing new energetic materials (EMs). H owever, there has been a lack of a quick and accurate method for evaluating the stability of diverse EMs.” Financial supporters for this research include Science and Technology Department of Sichuan Province, National Natural Science Foundation of China. Our news editors obtained a quote from the research from Sichuan University, “He re, we develop a machine learning prediction model with high accuracy for bond d issociation energy (BDE) of EMs. A reliable and representative BDE dataset of EM s is constructed by collecting 778 experimental energetic compounds and quantum mechanics calculation. To sufficiently characterize the BDE of EMs, a hybrid fea ture representation is proposed by coupling the local target bond into the globa l structure characteristics. To alleviate the limitation of the low dataset, pai rwise difference regression is utilized as a data augmentation with the advantag e of reducing systematic errors and improving diversity.”
ChengduPeople’s Republic of ChinaAsi aCyborgsEmerging TechnologiesMachine LearningSichuan University
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