Estimation, decoding and forecasting in HMM and hybrid HMM/ANN models: a case of seismic events in Poland
Estimation, decoding and forecasting in HMM and hybrid HMM/ANN models: a case of seismic events in Poland
This paper compares performance of a hidden Markov model (HMM) and a hybrid HMM/ANN model in seismic events modeling. Observation variables are assumed to follow a Poisson distribution. Parameters of the discrete-time two-state models are estimated on the basis of data on seismic events that were recorded in Poland from 1991 to 1995. Then, on the basis of the estimation results, the most likely sequences of states of the hidden Markov chains are found and forecasts for January 1996 are made. It is shown that the hybrid model fits better to the data.
Hidden Markov models, hybrid HMM/ANN models, neural networks, seismic events
7-17
Bijak, Katarzyna
5130b6b9-fbf1-44e8-9106-1dd69c6692a6
2006
Bijak, Katarzyna
5130b6b9-fbf1-44e8-9106-1dd69c6692a6
Bijak, Katarzyna
(2006)
Estimation, decoding and forecasting in HMM and hybrid HMM/ANN models: a case of seismic events in Poland.
Studia Informatica, 1/2 (7), .
Abstract
This paper compares performance of a hidden Markov model (HMM) and a hybrid HMM/ANN model in seismic events modeling. Observation variables are assumed to follow a Poisson distribution. Parameters of the discrete-time two-state models are estimated on the basis of data on seismic events that were recorded in Poland from 1991 to 1995. Then, on the basis of the estimation results, the most likely sequences of states of the hidden Markov chains are found and forecasts for January 1996 are made. It is shown that the hybrid model fits better to the data.
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Published date: 2006
Keywords:
Hidden Markov models, hybrid HMM/ANN models, neural networks, seismic events
Organisations:
Centre of Excellence for International Banking, Finance & Accounting
Identifiers
Local EPrints ID: 361319
URI: http://eprints.soton.ac.uk/id/eprint/361319
PURE UUID: e7be2c3d-441f-4ec4-8a2b-a9673c998d81
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Date deposited: 22 Jan 2014 12:09
Last modified: 11 Dec 2021 04:27
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