@inproceedings{1afd69b936874b0c8525b07fca1ea767,
title = "MKLS-SVR based remaining useful life prediction for avionics",
abstract = "The avionic equipments are important parts of aircraft. Their failures take higher proportion in the total failure, which affect the performance of the whole system. A prediction model based on Multiple Kernel LS-SVR (MKLS-SVR) is proposed in this paper and used for remaining using life (RUL) prediction with a certain avionic device. The simulation results show that the MKLS-SVR has a higher accuracy comparing with the traditional LS-SVR, and it is a practical and effective electronic equipment RUL prediction method.",
keywords = "Avionic equipments, LS-SVR, Multiple Kernel Learning, Prediction, Remaining using life",
author = "Yangming Guo and Pei He and Hao Wu and Jiaqi Zhang and Zige Wang and Xuefeng Jiang and Junrui Liu",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2015 ; Conference date: 16-07-2015 Through 18-07-2015",
year = "2016",
month = jun,
day = "16",
doi = "10.1109/ICEMI.2015.7494257",
language = "英语",
series = "2015 IEEE 12th International Conference on Electronic Measurement and Instruments, ICEMI 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "223--227",
editor = "Cui Jianping and Wu Juan",
booktitle = "2015 IEEE 12th International Conference on Electronic Measurement and Instruments, ICEMI 2015",
}