Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information

• Published in: Di xue qian yuan. Vol. 9; no. 6; pp. 1679 - 1687
• Main Authors: Li, Xueyou, Zhang, Limin, Zhang, Shuai
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier B.V 01.11.2018; Elsevier Science Ltd; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China; Elsevier
• Subjects: Bayesian analysis; Bayesian networks; Big Data; Material properties; Monitoring; Monitoring information; Risk management; Safety; Slope reliability; Slope stability; Value of information; Wireless networks; Monitoring information; Big data; Bayesian networks; Risk management; Value of information; Slope reliability
• ISSN: 1674-9871; 2588-9192
• DOI: 10.1016/j.gsf.2017.09.009

New sensing and wireless technologies generate massive data. This paper proposes an efficient Bayesian network to evaluate the slope safety using large-quantity field monitoring information with underlying physical mechanisms. A Bayesian network for a slope involving correlated material properties and dozens of observational points is constructed. [Display omitted] •New sensing and wireless technologies generate massive monitoring data.•This paper proposes an efficient Bayesian network to evaluate the slope safety.•Large-quantity field monitoring information is integrated in the evaluation.•A Bayesian network for a slope involving correlated properties is constructed.•The value of information has also been evaluated in the Bayesian network.