New Findings on Machine Learning Described by Investigators at Liaoning Universi ty of Technology (Compressive Strength Prediction of Cement Base Under Sulfate A ttack By Machine Learning Approach)
New Findings on Machine Learning Described by Investigators at Liaoning Universi ty of Technology (Compressive Strength Prediction of Cement Base Under Sulfate A ttack By Machine Learning Approach)
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingoriginating in Jinzhou, People’s Rep ublic of China, by NewsRx journalists, research stated, “Cementbasedmaterials in underground structures, bridge foundation, and offshore platforms often face sulfate environments. It has been widely reported that the compressive strength (CS) of these materials postsulfate attack is crucial for structural stability and durability.”
Key words
Jinzhou/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Liaoning University of Tech nology
NETL
NSTL