首页|Investigators at Jinhua Polytechnic Detail Findings in Machine Learning (Applica tion of Machine Learning Boosting and Bagging Methods To Predict Compressive and Flexural Strength of Marble Cement Mortar)
Investigators at Jinhua Polytechnic Detail Findings in Machine Learning (Applica tion of Machine Learning Boosting and Bagging Methods To Predict Compressive and Flexural Strength of Marble Cement Mortar)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news reporting originating from Zhejiang, People’ s Republic of China, by NewsRx editors, the research stated, “Compressive (CS) a nd flexural strength (FS) of sustainable mortar made from waste materials were e stimated using machine learning (ML) tools. Ensemble ML techniques, including ex treme gradient boosting (XGB) and bagging regressor (BR), were utilized to accom plish the study goals.”
ZhejiangPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningJinhua Polytechnic
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