首页|Findings on Machine Learning Reported by Investigators at Xi’an University (Machine Learning Based Prediction Model for the Pile Bearing Capacity of Saline Soils In Cold Regions)
Findings on Machine Learning Reported by Investigators at Xi’an University (Machine Learning Based Prediction Model for the Pile Bearing Capacity of Saline Soils In Cold Regions)
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NETL
NSTL
Elsevier
Investigators discuss new findings in Machine Learning. According to news reporting originating from Xi’an, People’s Republic of China, by NewsRx correspondents, research stated, “The difficulty in determining the bearing capacity of pile foundations in saline soil environments in cold regions can pose a challenge when developing a bearing capacity prediction model. To address this, the study uses data from the construction of the De Xiang Expressway project in Qinghai Province, China, and considers pile length, pile diameter, corrosion depth, and spalling thickness as influential parameters.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), Qinghai Provincial Highway and Traffic Science and Technology Research Project.
Xi’anPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningXi’an University
NETL
NSTL
Elsevier
