Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)

Study and Application on the Method of Association Rules Mining Based on Genetic Algorithm

Authors
Xinhang Xu, Hongtao Zhang, Lei Wang, Yonghong Liu, Qiuhong Sun
Corresponding Author
Xinhang Xu
Available Online August 2012.
DOI
10.2991/iccasm.2012.73How to use a DOI?
Keywords
Association Rules, Genetic Algorithm, Fitness Function
Abstract

This article is mainly discussing the application of genetic algorithms to data mining of association rules, and proposing method of extract association rules using genetic algorithm, at the same time discussing genetic algorithm coding methods and construction of fitness function and improvement of genetic operator and so on. Given extraction algorithm of association rules based on genetic algorithm, and would be applied in hospital medical database in data mining.

Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
Series
Advances in Intelligent Systems Research
Publication Date
August 2012
ISBN
10.2991/iccasm.2012.73
ISSN
1951-6851
DOI
10.2991/iccasm.2012.73How to use a DOI?
Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Xinhang Xu
AU  - Hongtao Zhang
AU  - Lei Wang
AU  - Yonghong Liu
AU  - Qiuhong Sun
PY  - 2012/08
DA  - 2012/08
TI  - Study and Application on the Method of Association Rules Mining Based on Genetic Algorithm
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 293
EP  - 295
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.73
DO  - 10.2991/iccasm.2012.73
ID  - Xu2012/08
ER  -