Dynamic evidential reasoning algorithm for systems reliability prediction

References

• Ascher , H and Hung , S . 1987 . Repairable System Reliability , New York : Marcel Dekker Inc .
   Google Scholar
• Box , GE and Jenkins , GM . 1970 . Time Series Analysis Forecasting and Control , San Francisco : Holden-Day .
   Google Scholar
• Chang, P.T., Lin, K.P., and Pai, P.F. (2004), ‘Hybrid Learning Fuzzy Neural Models in Forecasting Engine Systems Reliability’, in Proceeding of the Fifth Asia Pacific Industrial Engineering and Management Systems Conference, Australia, Gold Coast, pp. 2361–2366.
   Google Scholar
• Chen , KY . 2007 . Forecasting Systems Reliability Based on Support Vector Regression with Genetic Algorithms . Reliability Engineering and System Safety , 92 : 423 – 432 .
   Web of Science ®Google Scholar
• Connor , JT , Martin , D and Atlas , LE . 1994 . Recurrent Neural Networks and Robust Time Series Prediction . IEEE Transactions on Neural Networks , 5 : 240 – 254 .
   PubMed Web of Science ®Google Scholar
• Dempster , AP . 1967 . Upper and Lower Probabilities Induced by a Multi-Valued Mapping . Annals Mathematical Statistics , 38 : 325 – 339 .
   Google Scholar
• Falk , B and Roy , A . 2005 . Forecasting Using the Trend Model with Autoregressive Errors . International Journal of Forecasting , 21 : 291 – 302 .
   Google Scholar
• Ho , SL and Xie , M . 1998 . The Use of ARIMA Models for Reliability Forecasting and Analysis . Computer and Industrial Engineering , 35 : 213 – 216 .
   Web of Science ®Google Scholar
• Hu, C.H., Si, X.S., Yang, J.B., and Zhou, Z.J., (2008), ‘On the Dynamic Evidential Reasoning Algorithm for Fault Prediction’. IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, accepted with major revisions.
   Google Scholar
• Liang , T and Afzel , N . 2005 . Evolutionary Neural Network Modeling for Software Cumulative Failure Time Prediction . Reliability Engineering and System Safety , 87 : 45 – 51 .
   Google Scholar
• Liang , T and Afzel , N . 2006 . Reply to ‘Comment on “Evolutionary Neural Network modeling for Software Cumulative Failure Time Prediction” by Liang Tian and Afzel Noore”, by Bev Littlewood . Reliability Engineering and System Safety , 91 : 487 – 491 .
   Google Scholar
• Liang , YH . 2007 . Evolutionary Neural Network Modelling for Forecasting the Field Failure Data of Repairable Systems . Expert Systems with Applications , 33 : 1090 – 1096 .
   Google Scholar
• Liang , YH and Tong , LI . 2001 . Analyzing and Forecasting the Field Failure Data for Repairable Systems . Journal of Quality , 8 : 75 – 96 .
   Google Scholar
• Liu , J , Yang , JB , Ruan , D , Martinez , L and Wang , J . 2008 . Self-Tuning of Fuzzy Belief Rule Bases for Engineering System Safety Analysis . Annals Operational Research , 163 : 143 – 168 .
   Web of Science ®Google Scholar
• Liu , J , Yang , JB , Wang , J , Sii , HS and Wang , YM . 2004 . Fuzzy Rule-Based Evidential Reasoning Approach for Safety Analysis . International Journal of General Systems , 33 : 183 – 204 .
   Web of Science ®Google Scholar
• Nelson , W . 1988 . Applied Life Data Analysis , New York : Wiley .
   Google Scholar
• Niu , G and Yang , BS . 2009 . Dempster-Shafer Regression for Multi-Step-Ahead Time-Series Prediction Towards Data-Driven Machinery Prognosis . Mechanical Systems and Signal Processing , 23 : 740 – 751 .
   Google Scholar
• Pai , PF . 2006 . Systems Reliability Forecasting Based on Support Vector Machines with Genetic Algorithms . Mathematical and Computer Modelling , 43 : 262 – 247 .
   Web of Science ®Google Scholar
• Peddle , DR . 1995 . Mercury : An Evidential Reasoning Image Classifier . Computer and Geosciences , 21 : 1163 – 1173 .
   Web of Science ®Google Scholar
• Petit-Renaud , S and Denoeux , T . 2004 . Nonparametric Regression Analysis of Uncertain and Imprecise Data Using Belief Functions . International Journal of Approximate Reasoning , 35 : 1 – 28 .
   Google Scholar
• Sanz, C. (2001), ‘DER (Dynamic Evidential Reasoning), Applied to the Classification of Hyperspectral Images’, in Geoscience and Remote Sensing Symposium, Australia, Sydney, pp. 1904–1906.
   Google Scholar
• Shafer , G . 1976 . A Mathematical Theory of Evidence , New Jersey : Princeton University Press .
   Google Scholar
• Singpurwala , ND . 1978 . Estimating Reliability Growth Using Time Series Analysis . Naval Research Logistics Quarterly , 25 : 1 – 14 .
   Google Scholar
• Singh , N , Chrys , DA and Frishwick , PA . 1994 . Forecasting Time-Dependent Failure Rates of Systems Operating in Series and/or in Parallel . Microelectronic Reliability , 34 : 391 – 400 .
   Web of Science ®Google Scholar
• Smets , P . 2007 . Analyzing the Combination of Conflicting Belief Functions . Information Fusion , 8 : 387 – 412 .
   Google Scholar
• Tong , LI and Liang , YH . 2005 . Forecasting Field Failure Data for Repairable Systems using Neural Networks and SARIMA Model . International Journal of Quality and Reliability Management , 22 : 410 – 420 .
   Google Scholar
• Wang , W . 2007 . An Adaptive Predictor for Dynamic Systems Forecasting . Mechanical Systems and Signal Processing , 21 : 809 – 823 .
   Google Scholar
• Wang , YM and Elhag , TMS . 2007 . A Comparison of Neural Network, Evidential Reasoning and Multiple Regression Analysis in Modeling Bridge Risks . Expert Systems and Applications , 32 : 336 – 348 .
   Web of Science ®Google Scholar
• Wang , YM and Elhag , TMS . 2008 . Evidential Reasoning Approach for Bridge Condition Assessment . Expert Systems with Applications , 34 : 689 – 699 .
   Web of Science ®Google Scholar
• Wang, J., Yang, T.B., and Sen, P. (1995), ‘Safety analysis and synthesis using fuzzy sets and evidential reasoning’, Reliability Engineering and Systems Safety, 47, 103–118.
   Google Scholar
• Wang, J., Yang, J.B., and Sen, P. (1996), ‘Multi-person and multi-attribute design evaluations using evidential reasoning based on subjective safety and cost analysis’, Reliability Engineering and Systems Safety, 52, 113–128.
   Google Scholar
• Wang , YM , Yang , JB and Xu , DL . 2006 . Environmental Impact Assessment Using the Evidential Reasoning Approach . European Journal of Operational Research , 174 : 1885 – 1913 .
   Web of Science ®Google Scholar
• Xu , DL , Liu , J , Yang , JB , Liu , GP , Wang , J , Jemkinson , I and Ren , J . 2007 . Inference and Learning Methodology of Belief-Rule-Based Expert System for Pipeline Leak detection . Expert Systems and Applications , 32 : 103 – 113 .
   Web of Science ®Google Scholar
• Xu. , K , Xie , M , Tang , LC and Ho , SL . 2003 . Application of Neural Networks in Forecasting Engine Reliability . Applied Soft Computing , 2 : 255 – 268 .
   Google Scholar
• Yang , JB . 2001 . Rule and Utility Based Evidential Reasoning Approach for Multi-Attribute Decision Analysis under Uncertainties . European Journal of Operational Research , 131 : 31 – 61 .
   Web of Science ®Google Scholar
• Yang , JB , Liu , J , Wang , J , Sii , HS and Wang , HW . 2006 . Belief Rule-Base inference Methodology Using the Evidential Reasoning Approach-RIMER . IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans , 30 : 266 – 285 .
   Google Scholar
• Yang , JB , Liu , J , Xu , DL , Wang , J and Wang , HW . 2007 . Optimization Models for Training Belief-Rule-Based Systems . IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans , 37 : 569 – 585 .
   Web of Science ®Google Scholar
• Yang , JB and Singh , MG . 1994 . An Evidential Reasoning Approach for Multiple-Attribute Decision Making with Uncertainty . IEEE Transactions on Systems, Man, and Cybernetics , 24 : 1 – 18 .
   Web of Science ®Google Scholar
• Yang , JB and Xu , DL . 2002a . On the Evidential Reasoning Algorithm for Multiple Attribute Decision Analysis under Uncertainty . IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans , 32 : 289 – 304 .
   Web of Science ®Google Scholar
• Yang , JB and Xu , DL . 2002b . Nonlinear Information Aggregation via Evidential Reasoning in Multiattribute Decision Analysis under Uncertainty . IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans , 32 : 376 – 393 .
   Web of Science ®Google Scholar