| Título: | Genetic Algorithms Principles Towards Hidden Markov Model |
| Autores: | Nabil M. Hewahi; Islamic University of Gaza, Palestine |
| Fecha: | 2011-10-10 |
| Publicador: | BRAIN: Broad Research in Artificial Intelligence and Neuroscience |
| Fuente: |
 |
| Tipo: | Peer-reviewed Article |
| Tema: |
Artificial Intelligence Hidden Markov Model; Genetic Algorithms |
| Descripción: | In this paper we propose a general approach based on Genetic Algorithms (GAs) to evolve Hidden Markov Models (HMM). The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to findout the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values. |
| Idioma: | Inglés |
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