Prediction of Dam Deformation Based on Self-adaptive MGM-Markov Model
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Abstract:
Dam deformation is influenced by a lot of factors. For those projects without long-term, continuous, and reliable monitoring data, the prediction precision of dam deformation based on the traditional MGM(1,n) model decreases with time. In this paper, the self-adaptive MGM(1,n) model was applied. The proposed model characterizes the interaction between each variable, and replaces the oldest information with new information, which can reflect the effects of random factors or perturbation on dam deformation. On the basis, the state transition probability matrix of the time series was determined by Markov chain, and the monitoring data and forecast data were analyzed to predict the dam deformation with a higher precision. Compared with the traditional MGM(1,n) model and self-adaptive MGM(1,n) model, the MGM-MC model has higher precision.
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