A Data-Driven Based Method for Pipeline Additional Stress Prediction Subject to Landslide Geohazards
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- Shucong Liu & Hongjun Wang & Rui Li & Beilei Ji, 2022. "A Novel Feature Identification Method of Pipeline In-Line Inspected Bending Strain Based on Optimized Deep Belief Network Model," Energies, MDPI, vol. 15(4), pages 1-19, February.
- Hao Pu & Jia Xie & Paul Schonfeld & Taoran Song & Wei Li & Jie Wang & Jianping Hu, 2021. "Railway Alignment Optimization in Mountainous Regions Considering Spatial Geological Hazards: A Sustainable Safety Perspective," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
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- Haibat Ali & Jae-ho Choi, 2019. "A Review of Underground Pipeline Leakage and Sinkhole Monitoring Methods Based on Wireless Sensor Networking," Sustainability, MDPI, vol. 11(15), pages 1-24, July.
- Wenhan Xu & Hong Xu & Jie Chen & Yanfei Kang & Yuanyuan Pu & Yabo Ye & Jue Tong, 2022. "Combining Numerical Simulation and Deep Learning for Landslide Displacement Prediction: An Attempt to Expand the Deep Learning Dataset," Sustainability, MDPI, vol. 14(11), pages 1-20, June.
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- Huseyin Ayhan Yavasoglu & Ilhami Unal & Ahmet Koksoy & Kursad Gokce & Yusuf Engin Tetik, 2023. "Long-Range Wireless Communication for In-Line Inspection Robot: 2.4 km On-Site Test," Sustainability, MDPI, vol. 15(10), pages 1-17, May.
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Keywords
oil and gas pipeline; landside monitoring; data-driven; pipeline additional stress; XGBoost;All these keywords.
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