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A hidden Markov model for earthquake prediction

机译:隐马尔可夫模型用于地震预报

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摘要

Earthquake occurrence is well-known to be associated with structural changes in underground dynamics, such as stress level and strength of electromagnetic signals. While the causation between earthquake occurrence and underground dynamics remains elusive, the modeling of changes in underground dynamics can provide insights on earthquake occurrence. However, underground dynamics are usually difficult to measure accurately or even unobservable. In order to model and examine the effect of the changes in unobservable underground dynamics on earthquake occurrence, we propose a novel model for earthquake prediction by introducing a latent Markov process to describe the underground dynamics. In particular, the model is capable of predicting the change-in-state of the hidden Markov chain, and thus can predict the time and magnitude of future earthquake occurrences simultaneously. Simulation studies and applications on a real earthquake dataset indicate that the proposed model successfully predicts future earthquake occurrences. Theoretical results, including the stationarity and ergodicity of the proposed model, as well as consistency and asymptotic normality of model parameter estimation, are provided.
机译:众所周知,地震的发生与地下动力学的结构变化有关,例如应力水平和电磁信号强度。尽管地震发生与地下动力学之间的因果关系仍然难以捉摸,但是地下动力学变化的建模可以提供有关地震发生的见解。但是,地下动力学通常难以准确测量甚至无法观测。为了建模和检验不可观测的地下动力学变化对地震发生的影响,我们通过引入潜在的马尔可夫过程来描述地下动力学,提出了一种新的地震预测模型。特别地,该模型能够预测隐马尔可夫链的状态变化,从而可以同时预测未来地震发生的时间和震级。在真实地震数据集上的仿真研究和应用表明,所提出的模型成功地预测了未来的地震发生。提供了理论结果,包括所提出模型的平稳性和遍历性,以及模型参数估计的一致性和渐近正态性。

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