Comparison and Analysis of the Monte Carlo Simulation and GO Method for the Reliability of Equipment System

DOI

10.2991/isaeece-16.2016.5How to use a DOI?

Keywords

equipment; fault diagnosis; BP neural network; genetic algorithm

Abstract

Aiming at the problems of traditional BP neural network in fault diagnosis of equipment, the genetic algorithm is introduced to optimize the network, and the fault diagnosis model of equipment is established. The modeling ideas and considerations are introduced in detail, and the simulation calculation is carried out. The results show that the improved network has a good approximation performance, the training speed and accuracy are greatly improved, and it can be better to carry out fault diagnosis of equipment.

Copyright

© 2016, 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  - Xin Ren
PY  - 2016/04
DA  - 2016/04
TI  - Comparison and Analysis of the Monte Carlo Simulation and GO Method for the Reliability of Equipment System
BT  - Proceedings of the 2016 International Symposium on Advances in Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 24
EP  - 27
SN  - 2352-5401
UR  - https://doi.org/10.2991/isaeece-16.2016.5
DO  - 10.2991/isaeece-16.2016.5
ID  - Ren2016/04
ER  -