Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

Research on Network Optimization Based on Simulated Annealing Genetic Algorithm

Authors
Xinyun Chen
Corresponding Author
Xinyun Chen
Available Online April 2017.
DOI
10.2991/icmmct-17.2017.260How to use a DOI?
Keywords
simulated annealing algorithm, genetic algorithm, network optimization
Abstract

The practicability of the neural network is often affected by the network structure, needing optimization. We introduce the genetic algorithm into the simulated annealing algorithm to propose a new algorithm named the simulated annealing genetic algorithm, which combines the advantages of the two algorithms. The result shows that compared with the genetic algorithm and simulated annealing algorithm, the number of iterations of simulated annealing is fewer and the time of iterations is less.

Copyright
© 2017, 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 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/icmmct-17.2017.260
ISSN
2352-5401
DOI
10.2991/icmmct-17.2017.260How to use a DOI?
Copyright
© 2017, 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  - Xinyun Chen
PY  - 2017/04
DA  - 2017/04
TI  - Research on Network Optimization Based on Simulated Annealing Genetic Algorithm
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1349
EP  - 1354
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.260
DO  - 10.2991/icmmct-17.2017.260
ID  - Chen2017/04
ER  -