Efficient Bayesian networks for slope safety evaluation with large quantity monitoring information
Institution:
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong, China
Abstract:
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.