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• W3209964566 abstract "Slope failures are always frequent and important issues in surface mining, where a single calamity can disarrange mining schemes and endanger workers' lives. Simultaneously, the design and verification of landslide early warning systems in open-pit mines is a pivotal tool for mitigating risks. Notwithstanding, a prevalent model for heralding slope impending failures has not been available yet. The purpose of this article is to present a novel approach based on mean standard deviation (MSD) coupling weighted Markov chain (WMC) model to evaluate and perform the evolution that can detect onset-of-acceleration of landslides analysis procedure based on the indicator of real-time ground-based radar low-frequency measurements (e.g. displacement rate). The proposed method has been applied and tested in a open-pit coal mine situated in Inner Mongolia, China. An explanatory example of back analysis of a 4-month continuous surface monitoring dataset were regarded as a random process, and a binary classifier (i.e. steady-state and unsteady-state) was constructed based on the characteristics of mean standard deviation (MSD). Afterwards, properties of none aftereffect and bouncing allocation on the efficiency of Markov chains are studied. In order to modify and optimize the model, three indexes are integrated to verify the accuracy of the model and proof the predicting results: (1) precaution sensitiveness; (2) proper rate; (3) consensus rate. The consequences show that when the size of training samples was 20 days, the early warning accuracy reached 93%. When the model was performed seven days before the landslide occurrence, the true positive rate of the model was 84%, thus indicating the early warning for the landslide was timely. The integration of the proposed model and on-site monitoring data provides a useful tool for early warning of landslide displacement rates, and opens new perspectives on predicting slope instabilities." @default.
• W3209964566 created "2021-11-08" @default.
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• W3209964566 date "2021-10-01" @default.
• W3209964566 modified "2023-09-25" @default.
• W3209964566 title "Theoretical research of Stand Error of Mean Coupling Markov chain models for early warning of landslide displacement rates: A case study of human-induced landslide in Inner Mongolia (Northern China)" @default.
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• W3209964566 doi "https://doi.org/10.1088/1755-1315/861/6/062032" @default.
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