Abstract：
:The concept of chaos being radically different from statistical randomness is introduced into chemometrics research. The chaotic system that is deterministic with underlying patterns and inherent ability in searching the space of interest has been employed to improve the performance of chemometric algorithms. In this paper, a chaotic mutation is introduced into the genetic algorithm (GA) which is used for artificial neural network (ANN) training. The chaotic algorithm is very efficient in maintaining the population diversity during the evolution process of GA. The proposed algorithm CGANN has been testified by prediction of vibrational frequencies of octahedral hexahalides from some selected molecular parameters.
journal_name
Comput Biol Chemjournal_title
Computational biology and chemistryauthors
Lü Q,Shen G,Yu Rdoi
10.1016/s1476-9271(02)00083-xkeywords:
subject
Has Abstractpub_date
2003-07-01 00:00:00pages
363-71issue
3eissn
1476-9271issn
1476-928Xpii
S147692710200083Xjournal_volume
27pub_type
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journal_title：Computational biology and chemistry
pub_type： 杂志文章
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journal_title：Computational biology and chemistry
pub_type： 杂志文章
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更新日期：2005-12-01 00:00:00
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journal_title：Computational biology and chemistry
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journal_title：Computational biology and chemistry
pub_type： 杂志文章
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journal_title：Computational biology and chemistry
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journal_title：Computational biology and chemistry
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journal_title：Computational biology and chemistry
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journal_title：Computational biology and chemistry
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journal_title：Computational biology and chemistry
pub_type： 杂志文章
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