System reliability prediction model based on evidential reasoning algorithm with nonlinear optimization

被引:35
作者
Hu, Chang-Hua [1 ]
Si, Xiao-Sheng [1 ]
Yang, Jian-Bo [2 ]
机构
[1] Xian Inst Hitech, Dept Automat, Xian 710025, Shaanxi, Peoples R China
[2] Univ Manchester, Manchester Business Sch, Manchester M15 6PB, Lancs, England
基金
美国国家科学基金会;
关键词
Evidential reasoning; Reliability; Nonlinear optimization; Forecasting; MULTIATTRIBUTE DECISION-ANALYSIS; SUPPORT VECTOR MACHINES; NEURAL-NETWORK APPROACH; SOFTWARE-RELIABILITY; RULE; TIME; BELIEF; SAFETY; SERIES; REGRESSION;
D O I
10.1016/j.eswa.2009.08.024
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a novel reliability prediction technique based on the evidential reasoning (ER) algorithm is developed and applied to forecast reliability in turbocharger engine systems. The focus of this study is to examine the feasibility and validity of the ER algorithm in systems reliability prediction by comparing it with some existing approaches. To determine the parameters of the proposed model accurately, some nonlinear optimization models are investigated to search for the optimal parameters of forecasting model by minimizing the mean square error (MSE) criterion. Finally, a numerical example is provided to demonstrate the detailed implementation procedures. The experimental results show that the prediction performance of the ER-based prediction model outperforms several existing methods in terms of prediction accuracy or speed. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2550 / 2562
页数:13
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