Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)

Application of Immune Genetic Algorithm on Standard Library Building

Authors
Chunxia Yuan, Ke Yao
Corresponding Author
Chunxia Yuan
Available Online March 2019.
DOI
10.2991/iafsm-18.2019.10How to use a DOI?
Keywords
Fuzzy; Immune genetic algorithm; Standard library
Abstract

Based on the analysis of standard system construction current situation, this paper proposes an improved genetic algorithm by combining the fuzzy neural network and the immune genetic algorithm, which can be used to solve the standard feature vector clustering, and better overcomes the premature phenomenon of general intelligent algorithms. Furthermore, this paper also builds a service-oriented standards library, which takes standard feature vectors as the main clustering index. The practical experiment shows that this smart genetic algorithm, with strong robustness, reliability and accuracy, is of certain reference value to the standard system construction innovation and development.

Copyright
© 2019, 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 International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)
Series
Advances in Economics, Business and Management Research
Publication Date
March 2019
ISBN
978-94-6252-696-9
ISSN
2352-5428
DOI
10.2991/iafsm-18.2019.10How to use a DOI?
Copyright
© 2019, 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  - Chunxia Yuan
AU  - Ke Yao
PY  - 2019/03
DA  - 2019/03
TI  - Application of Immune Genetic Algorithm on Standard Library Building
BT  - Proceedings of the International Academic Conference on Frontiers in Social Sciences and Management Innovation (IAFSM 2018)
PB  - Atlantis Press
SP  - 62
EP  - 67
SN  - 2352-5428
UR  - https://doi.org/10.2991/iafsm-18.2019.10
DO  - 10.2991/iafsm-18.2019.10
ID  - Yuan2019/03
ER  -