Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Machine Learning have be en published. According to news reporting from Shenyang, People’s Republic of Ch ina, by NewsRx journalists, research stated, “In this study, a method combining physical metallurgical models with machine learning was used to design beta-type medical titanium alloys with low modulus of elasticity in Ti -Mo -Nb -Zr -Sn sy stem alloys. The prediction model used the Extreme Gradient Boosting (XGBoost) a lgorithm to predict the elastic modulus of the alloys, and the Mo equivalent (Mo eq value) and valence electron concentration ratio (e/a), which characterize the elastic modulus, were modeled as feature parameters that can improved the gener alization ability of the model and reduced overfitting.”
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