首页|New Machine Learning Study Findings Have Been Reported by Researchers at Beijing University of Technology (Prediction of the Sulfate Attack Resistance of Concre te Based On Machine-learning Algorithms)
New Machine Learning Study Findings Have Been Reported by Researchers at Beijing University of Technology (Prediction of the Sulfate Attack Resistance of Concre te Based On Machine-learning Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Data detailed on Machine Learning have been prese nted. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “The thorough investigation i nto the evolution of concrete performance under sulfate attack environments hold s significant importance for engineering applications in specific conditions. In this paper, a prediction model for the two evaluation indexes of sulfate attack resistance of concrete (SARC), namely compressive strength corrosion resistance coefficient and mass loss rate, is established based on four machine-learning a lgorithms: Support Vector Regression, Random Forest Regression, Gradient Boostin g, and Extreme Gradient Boosting (XGB).”
BeijingPeople’s Republic of ChinaAsi aAlgorithmsCyborgsEmerging TechnologiesMachine LearningBeijing Univers ity of Technology
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