Coal or Rock Eelectromagnetic Emission Analysis Based on Hidden Markov Model

Coal or rock electromagnetic emission analysis is a promising method for predicting coal or rock dynamic disasters. Hidden Markov Model (HMM) is applied to this problem in this paper. HMM model is a processing method of dynamic information based on probability, which can reflect both randomicity and...

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Bibliographic Details
Main Authors: Xiaobin Li, Jiansheng Qian, Nannan Lu, Can Cheng, Mingjun Dai, Shijie Shi
Format: Conference Proceeding
Language:English
Subjects:
Coal or Rock Electromagnetic Emission
Computational modeling
Data Mining
Electromagnetics
Hidden Markov
Hidden Markov models
Inspection
Markov processes
Rail transportation
Time Series
Time series analysis
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Summary:Coal or rock electromagnetic emission analysis is a promising method for predicting coal or rock dynamic disasters. Hidden Markov Model (HMM) is applied to this problem in this paper. HMM model is a processing method of dynamic information based on probability, which can reflect both randomicity and potential structure of the object. Model selecting of HMM Bayes Information Criterion is combined with classical optimization algorithm. Moreover, k-means clustering algorithm and Gaussian mixture model are introduced to initial HMM model. Researches in this paper indicate that HMM is an outstanding probability learning model which can perfectly analyse coal or rock electromagnetic emission time series problems.
DOI:10.1109/ICGEC.2010.34