An Improved Neural Network Optimization Method
Authors
Wen-long Yin, Tian-hui Zhang, Li-hua Guo, Jie Tao
Corresponding Author
Wen-long Yin
Available Online January 2015.
- DOI
- 10.2991/iccset-14.2015.6How to use a DOI?
- Keywords
- fiber optic gyro; temperature drift; artificial neural network; genetic algorithm
- Abstract
In order to solve the problem of temperature drift for fiber optic gyroscope, the neural network is used to construct the temperature drift model. The neural network is easy to fall into local minimum, the convergence speed is slow, the genetic algorithm is used to optimize neural network. The genetic algorithm has the problem of premature convergence is early in species, the mixed algorithm is used, the genetic algorithm is improved. The simulation results show that the neural network optimization method can predict the temperature of fiber optic gyroscope drift effectively.
- Copyright
- © 2015, 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 - Wen-long Yin AU - Tian-hui Zhang AU - Li-hua Guo AU - Jie Tao PY - 2015/01 DA - 2015/01 TI - An Improved Neural Network Optimization Method BT - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology PB - Atlantis Press SP - 27 EP - 30 SN - 2352-538X UR - https://doi.org/10.2991/iccset-14.2015.6 DO - 10.2991/iccset-14.2015.6 ID - Yin2015/01 ER -