An Improved Neural Network Optimization Method

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/).

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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  -