首页|Recent Studies from Texas A&M University Add New Data to Machine Le arning (Mechanisms of Extensive Fracture Propagation Post-coalescence: a Machine Learning Assisted Discovery)
Recent Studies from Texas A&M University Add New Data to Machine Le arning (Mechanisms of Extensive Fracture Propagation Post-coalescence: a Machine Learning Assisted Discovery)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting originating from College Station, Texas, by NewsRx correspondents, research stated, “This study investigates the sp atial arrangement of existing crack pathways and the crack network at the time o f crack coalescence in brittle rock -like materials, focusing on the factors tha t contribute to rapid and extensive crack growth immediately afterward. To that end, we extract relevant informative features from simulated crack networks gene rated by the HOSS simulator and employ machine learning methods to establish cor relations between these features and the initiation of rapid and extensive crack propagation following coalescence.”
College StationTexasUnited StatesN orth and Central AmericaCyborgsEmerging TechnologiesMachine LearningTexas A&M University
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