Abstract
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).”
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