Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Genetic Algorithm Theory and Its Application

Authors
Shaojun Yi, Shengliang Zou
Corresponding Author
Shaojun Yi
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.90How to use a DOI?
Keywords
Genetic algorithm; Theory; Application
Abstract
Genetic Algorithm (GA) is a very effective optimization solution method. It can provide faster and better results than some traditional optimization methods for the control structures and control functions in the control field. It can be said that the intelligent connection of GA and CAD software packages for high-precision system modeling and controller automation design and parameter optimization will be a new and effective method. The current evolution of GA learning in human beings is still formal. It has not yet been able to portray the evolutionary process of human beings. It has failed to portray the true learning process of neuron thinking.
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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.90How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Shaojun Yi
AU  - Shengliang Zou
PY  - 2018/05
DA  - 2018/05
TI  - Genetic Algorithm Theory and Its Application
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.90
DO  - https://doi.org/10.2991/amcce-18.2018.90
ID  - Yi2018/05
ER  -