Monitoring and early warning of a metal mine tailings pond based on a deep learning bidirectional recurrent long and short memory network.

ABSTRACT: The effective monitoring and early warning capability of metal mine tailings ponds can improve the associated safety risk management level. The infiltration line is an important core index of tailings pond stability. In this paper, a tailings pond monitoring and early warning system, which provides technical support for the design and daily management of tailings reservoir early warning systems, is constructed. Based on a deep learning bidirectional recurrent long and short memory network, an infiltration line prediction model with univariate input and an infiltration line prediction model with multivariate input are proposed. The data adopted are those from four monitoring points of the same cross-section at different positions and data from one adjacent internal lateral displacement and

SUBMITTER: Jing Z 

PROVIDER: S-EPMC9562152 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature