@inproceedings{c9521dfe4aaa431da4016fc79458a602,
title = "Reliability approximation evaluation of multi-stated weighted k-out-of-n systems",
abstract = "The multi-stated weighted k-out-of-n (majority) systems are widely applied in various scenarios such as industrial or military applications where the ability of fault-tolerance is desirable. In this paper, a stochastic multiple-valued approach (SMVA) is proposed in order to evaluate the system efficiently. The weights and reliabilities of multi-state components are represented by stochastic sequences which are composed of fixed number of multi-valued numbers with the position being randomly permutated. The reliability analysis of multi-stated majority system indicates that the proposed SMVA is more efficient than the analysis through adopting universal generating functions or fuzzy universal generating functions.",
keywords = "fuzzy universal generating function, multi-stated majority system, stochastic multi-valued approach, universal generating function",
author = "Xiaogang Song and Zhengjun Zhai and Peican Zhu and Yangming Guo and Yunpeng Zhang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 8th IEEE Prognostics and System Health Management Conference, PHM-Harbin 2017 ; Conference date: 09-07-2017 Through 12-07-2017",
year = "2017",
month = oct,
day = "20",
doi = "10.1109/PHM.2017.8079134",
language = "英语",
series = "2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Bin Zhang and Yu Peng and Haitao Liao and Datong Liu and Shaojun Wang and Qiang Miao",
booktitle = "2017 Prognostics and System Health Management Conference, PHM-Harbin 2017 - Proceedings",
}