首页|Studies from University of Science and Technology Beijing in the Area of Machine Learning Described (Crack Pattern Identification In Cementitious Materials Base d On Acoustic Emission and Machine Learning)
Studies from University of Science and Technology Beijing in the Area of Machine Learning Described (Crack Pattern Identification In Cementitious Materials Base d On Acoustic Emission and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news originating from Beijing, People's Repu blic of China, by NewsRx correspondents, research stated, "The cracking patterns in cementitious materials before failure are closely related to acoustic emissi on (AE) monitoring signals. Traditional rise angle -average frequency analysis m ethods rely on empirical judgment for boundary line determination, lacking effec tive automated recognition methods to distinguish between tensile, shear, and mi xed crack types."
BeijingPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSupport Vector MachinesUn iversity of Science and Technology Beijing
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