Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information
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 a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2018-11-01
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| Series: | Geoscience Frontiers |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1674987117301652 |
| _version_ | 1797709784333418496 |
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| author | Xueyou Li Limin Zhang Shuai Zhang |
| author_facet | Xueyou Li Limin Zhang Shuai Zhang |
| author_sort | Xueyou Li |
| collection | DOAJ |
| description | 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. Keywords: Slope reliability, Monitoring information, Bayesian networks, Risk management, Value of information, Big data |
| first_indexed | 2024-03-12T06:42:52Z |
| format | Article |
| id | doaj.art-0b7be786766f441f9181fee8562a4006 |
| institution | Directory Open Access Journal |
| issn | 1674-9871 |
| language | English |
| last_indexed | 2024-03-12T06:42:52Z |
| publishDate | 2018-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Geoscience Frontiers |
| spelling | doaj.art-0b7be786766f441f9181fee8562a40062023-09-03T00:50:29ZengElsevierGeoscience Frontiers1674-98712018-11-019616791687Efficient Bayesian networks for slope safety evaluation with large quantity monitoring informationXueyou Li0Limin Zhang1Shuai Zhang2Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, ChinaCorresponding author.; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, ChinaDepartment of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, ChinaNew 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. Keywords: Slope reliability, Monitoring information, Bayesian networks, Risk management, Value of information, Big datahttp://www.sciencedirect.com/science/article/pii/S1674987117301652 |
| spellingShingle | Xueyou Li Limin Zhang Shuai Zhang Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information Geoscience Frontiers |
| title | Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information |
| title_full | Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information |
| title_fullStr | Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information |
| title_full_unstemmed | Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information |
| title_short | Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information |
| title_sort | efficient bayesian networks for slope safety evaluation with large quantity monitoring information |
| url | http://www.sciencedirect.com/science/article/pii/S1674987117301652 |
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