Guo, H.; Cui, D.; Li, Q.; Chen, Q.; Lai, L. Prediction and Reliability Analysis of the Pressuremeter Modulus of the Deep Overburden in Hydraulic Engineering Based on Machine Learning and Physical Mechanisms. Appl. Sci. 2025, 15, 10643. https://doi.org/10.3390/app151910643

AMA Style

Guo H, Cui D, Li Q, Chen Q, Lai L. Prediction and Reliability Analysis of the Pressuremeter Modulus of the Deep Overburden in Hydraulic Engineering Based on Machine Learning and Physical Mechanisms. Applied Sciences. 2025; 15(19):10643. https://doi.org/10.3390/app151910643

Chicago/Turabian Style

Guo, Hanyu, Deshan Cui, Qingchun Li, Qiong Chen, and Lin Lai. 2025. "Prediction and Reliability Analysis of the Pressuremeter Modulus of the Deep Overburden in Hydraulic Engineering Based on Machine Learning and Physical Mechanisms" Applied Sciences 15, no. 19: 10643. https://doi.org/10.3390/app151910643

APA Style

Guo, H., Cui, D., Li, Q., Chen, Q., & Lai, L. (2025). Prediction and Reliability Analysis of the Pressuremeter Modulus of the Deep Overburden in Hydraulic Engineering Based on Machine Learning and Physical Mechanisms. Applied Sciences, 15(19), 10643. https://doi.org/10.3390/app151910643

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

For more information on the journal statistics, click here.

Multiple requests from the same IP address are counted as one view.

Article Menu

Article Versions Notes

Further Information

Guidelines

MDPI Initiatives

Follow MDPI