Studies from Army Engineering University of PLA Provide New Data on Machine Lear ning (Buckling critical load prediction of pultruded fiber-reinforced polymer co lumns and feature analysis by machine learning)
Studies from Army Engineering University of PLA Provide New Data on Machine Lear ning (Buckling critical load prediction of pultruded fiber-reinforced polymer co lumns and feature analysis by machine learning)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on artificial intelligence is now available. According to news reporting out of Nanjing, People's Republic of China, by NewsRx editors, research stated, "For slender FRP columns, predict ing the global buckling critical loads is crucial in structural design." Funders for this research include National Natural Science Foundation of China. Our news journalists obtained a quote from the research from Army Engineering Un iversity of PLA: "However, there is a lack of a consensus prediction method base d on specialized domain knowledge. To address this issue, this study created a c omprehensive database by collecting 365 experimental data related to global buck ling of axially loaded pultruded FRP columns to predict buckling critical loads using such machine learning methods as extreme gradient boosting, artificial neu ral network, and support vector regression. The prediction accuracy and stabilit y of the machine learning prediction methods were evaluated, and the interpretab ility of the features was analyzed in depth. The results show that the predictio n accuracy of the traditional theoretical methods is low, while that of the mach ine learning methods is high. The contribution of geometric parameters to the bu ckling critical load is more than 80 %."
Key words
Army Engineering University of PLA/Nanj ing/People's Republic of China/Asia/Cyborgs/Emerging Technologies/Machine L earning
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