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  • 标题:Genetic Algorithms Principles Towards Hidden Markov Model
  • 本地全文:下载
  • 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:pp-11"
  • 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
  • 关键词:Hidden Markov Model
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