文章基本信息

标题：Genetic Algorithms Principles Towards Hidden Markov Model
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作者：Nabil M. Hewahi
期刊名称：Brain. Broad Research in Artificial Intelligence and Neuroscience
印刷版ISSN：2067-3957
出版年度：2011
卷号：2
期号：3
页码：5-11
语种：English
出版社：EduSoft publishing
摘要：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 find out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.
关键词：Hidden Markov Model;Genetic Algorithms