首页|Data on Machine Learning Reported by Researchers at School of Resources & Safety Engineering (Risk Assessment of Rockburst Using Smote Oversampling and In tegration Algorithms Under Gbdt Framework)
Data on Machine Learning Reported by Researchers at School of Resources & Safety Engineering (Risk Assessment of Rockburst Using Smote Oversampling and In tegration Algorithms Under Gbdt Framework)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Investigators publish new report on Machine Learn ing. According to news reporting out ofChangsha, People’s Republic of China, by NewsRx editors, research stated, “Rockburst is a commongeological disaster in underground engineering, which seriously threatens the safety of personnel, equipment and property. Utilizing machine learning models to evaluate risk of rockbu rst is gradually becominga trend.”
ChangshaPeople’s Republic of ChinaAs iaAlgorithmsCyborgsEmerging TechnologiesMachine LearningSchool of Reso urces & Safety Engineering
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