首页|New Data from Chongqing Jiaotong University Illuminate Findings in Machine Learning (Hybrid Xgb Model for Predicting Unconfined Compressive Strength of Solid Waste-cement-stabilized Cohesive Soil)
New Data from Chongqing Jiaotong University Illuminate Findings in Machine Learning (Hybrid Xgb Model for Predicting Unconfined Compressive Strength of Solid Waste-cement-stabilized Cohesive Soil)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news originating from Chongqing, People’s Republic of China, by NewsRx correspondents, research stated, “The utilization of cement has been found to have negative environmental impacts. In order to reduce the quantity of cement used and improve the mechanical properties of solid waste-cement-st abilized cohesive soil, the incorporation of solid waste as additives has been investigated.”
ChongqingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningChongqing Jiaotong University
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