@inproceedings{e543cc229ae84e49b5fbfe0541a80f1a,
title = "Research of a fault prediction method of the electronic equipment based on arma - Elman neural network model",
abstract = "To improve the accuracy of the fault prediction of the electronic equipment, a novel fault prediction method based on ARMA-Elman neural network model is presented. The ARMA- Elman neural network model combines the fitting ability of ARMA model to linear time series with the mapping ability of Elman neural network to nonlinear time series. The forecasting model is tested by the actual data from high-voltage power supply of radar transmitter. Simulation result shows that the prediction accuracy of ARMA-Elman neural network model has better prediction accuracy than the single ARMA model and Elman neural network model. So this method is feasible and effective.",
keywords = "Combined-model, Electronic-equipment, Elman-neural-network, Fault-prediction",
author = "Xiaodong Liu and Jinyu Deng and Jingli Yang and Yue Li",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2018 ; Conference date: 19-07-2018 Through 21-07-2018",
year = "2018",
month = jul,
doi = "10.1109/IMCCC.2018.00376",
language = "英语",
series = "Proceedings - 8th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1827--1830",
editor = "Jun-Bao Li",
booktitle = "Proceedings - 8th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2018",
address = "美国",
}