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100   $a20160829d2010      uy 
101 0 $aeng
135   $aur|||||||||||
181   $ctxt
182   $cc
183   $acr
200 10$a2010 Fourth International Conference on Genetic and Evolutionary Computing
210 31$a[Place of publication not identified]$cI E E E$d2010
215   $a1 online resource
300   $aBibliographic Level Mode of Issuance: Monograph
311 08$a9781424488919 
311 08$a1424488915 
330   $aCoal 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.
606   $aEvolutionary computation$vCongresses
615  0$aEvolutionary computation
676   $a005.432
702   $aIEEE Staff
801  0$bPQKB
906   $aPROCEEDING
912   $a9910139156203321
996   $a2010 Fourth International Conference on Genetic and Evolutionary Computing$92349678
997   $aUNINA