首页|Findings from Wuhan University of Technology Provide New Insights into Machine L earning (Estimation and Interpretation of Interfacial Bond In Concrete-filled St eel Tube By Using Optimized Xgboost and Shap)
Findings from Wuhan University of Technology Provide New Insights into Machine L earning (Estimation and Interpretation of Interfacial Bond In Concrete-filled St eel Tube By Using Optimized Xgboost and Shap)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on Machine Learning is now available. According to news reportingoriginating in Sanya, People’s Republic of China, by NewsRx journalists, research stated, “In view of thedifficulty in establishing an accurate mathematical model to characterize the interfacial bond strength inconcrete-filled steel tube (CFST), the ‘eXtreme Gradient Boosting’ (XGBoost) is utilized as a computationaltool for capturing the bond behavior in this paper. The water-to-cement ratio and concrete compressivestrength are tak en as input variables, as well as strength grade, length, thickness and diameter of steeltube and a generalization coefficient.”
SanyaPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningWuhan University of Technolog y
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