首页|Researchers from School of Civil Engineering Report Recent Findings in Machine L earning (Prediction and Analysis of Damage To Rc Columns Under Close-in Blast Lo ads Based On Machine Learning and Monte Carlo Method)
Researchers from School of Civil Engineering Report Recent Findings in Machine L earning (Prediction and Analysis of Damage To Rc Columns Under Close-in Blast Lo ads Based On Machine Learning and Monte Carlo Method)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-Current study results on Machine Learn ing have been published. According tonews reporting from Hunan, People's Republ ic of China, by NewsRx journalists, research stated, "Rapidprediction and quant itative assessment of the damage of reinforced concrete (RC) columns under blastloads are challenging and crucial issues. The key parameters affecting the anti -blast capacity of RCcolumns are coupled with failure modes."The news correspondents obtained a quote from the research from the School of Ci vil Engineering,"In this study, machine learning (ML) and Monte Carlo (MC) simu lations are employed to investigatethe damage of RC columns subjected to blast loads. 257 data collected from existing experimental andnumerical studies are u tilized to establish a database for model training and testing. The damage indexes of columns are predicted using eight ML models with eight input features. The predictive capacity of each model is characterized by eight evaluation indexes through MC simulations. The CatBoost model isidentified as the optimal model ba sed on the Analytic Hierarchy Process (AHP). Additionally, the CatBoostmodel is explained using the SHapley Additive exPlanations (SHAP) method, and the influe nce of axialcompression ratio on column damage is determined to be intricate. T he coupling relationship betweenthe axial compression ratio and the scale dista nce of the column is analyzed. Finally, a zonal diagram isdeveloped."
HunanPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSchool of Civil Engineering
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