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

机译:带有大量监控信息的高效贝叶斯网络,用于边坡安全评估

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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. Graphical abstract Display Omitted Highlights ? 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.
机译:新的传感和无线技术会生成大量数据。本文提出了一种有效的贝叶斯网络,利用具有潜在物理机制的大量现场监测信息来评估边坡安全性。针对涉及相关材料属性和数十个观测点的边坡,建立了贝叶斯网络。图形摘要显示省略的突出显示?新的传感和无线技术会生成大量的监视数据。 ?本文提出了一种有效的贝叶斯网络来评估边坡安全性。 ?评估中集成了大数量的现场监视信息。 ?针对涉及相关属性的边坡,构造了贝叶斯网络。 ?信息的价值也在贝叶斯网络中得到了评估。

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