A new method for analysis of Multi-State systems based on Multi-valued decision diagram under epistemic uncertainty
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DOI: 10.1016/j.ress.2022.108868
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- Zio, Enrico, 2022. "Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
- Jung, Yongsu & Jo, Hwisang & Choo, Jeonghwan & Lee, Ikjin, 2022. "Statistical model calibration and design optimization under aleatory and epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
- Saeed, Umer & Jan, Sana Ullah & Lee, Young-Doo & Koo, Insoo, 2021. "Fault diagnosis based on extremely randomized trees in wireless sensor networks," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
- Wang, Yanzhong & Xie, Bin & E, Shiyuan, 2022. "Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
- Liang, Qingzhu & Yang, Yinghao & Zhang, Hang & Peng, Changhong & Lu, Jianchao, 2022. "Analysis of simplification in Markov state-based models for reliability assessment of complex safety systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
- Hernandez-Perdomo, Elvis & Guney, Yilmaz & Rocco, Claudio M., 2019. "A reliability model for assessing corporate governance using machine learning techniques," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 220-231.
- Andrés Ruiz-Tagle Palazuelos & Enrique López Droguett & Rodrigo Pascual, 2020. "A novel deep capsule neural network for remaining useful life estimation," Journal of Risk and Reliability, , vol. 234(1), pages 151-167, February.
- Sarazin, Gabriel & Morio, Jérôme & Lagnoux, Agnès & Balesdent, Mathieu & Brevault, Loïc, 2021. "Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
- Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
- Xing, Jinduo & Zeng, Zhiguo & Zio, Enrico, 2019. "A framework for dynamic risk assessment with condition monitoring data and inspection data," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
- Nguyen, Khanh T.P. & Medjaher, Kamal, 2019. "A new dynamic predictive maintenance framework using deep learning for failure prognostics," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 251-262.
- Rachman, Andika & Ratnayake, R.M. Chandima, 2019. "Machine learning approach for risk-based inspection screening assessment," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 518-532.
- Enrico Zio & Piero Baraldi & Irina C. Popescu, 2008. "A Fuzzy Decision Tree for Fault Classification," Risk Analysis, John Wiley & Sons, vol. 28(1), pages 49-67, February.
- Azizpour, Hooshyar & Lundteigen, Mary Ann, 2019. "Analysis of simplification in Markov-based models for performance assessment of Safety Instrumented System," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 252-260.
- Ibáñez-Llano, Cristina & Rauzy, Antoine & Meléndez, Enrique & Nieto, Francisco, 2010. "Hybrid approach for the assessment of PSA models by means of binary decision diagrams," Reliability Engineering and System Safety, Elsevier, vol. 95(10), pages 1076-1092.
- Constâncio António Pinto & José Torres Farinha & Hugo Raposo & Diego Galar, 2022. "Stochastic versus Fuzzy Models—A Discussion Centered on the Reliability of an Electrical Power Supply System in a Large European Hospital," Energies, MDPI, vol. 15(3), pages 1-21, January.
- Mo, Yuchang & Xing, Liudong & Cui, Lirong & Si, Shubin, 2017. "MDD-based performability analysis of multi-state linear consecutive-k-out-of-n: F systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 124-131.
- Kvassay, Miroslav & Zaitseva, Elena & Levashenko, Vitaly, 2017. "Importance analysis of multi-state systems based on tools of logical differential calculus," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 302-316.
- Salomon, Julian & Winnewisser, Niklas & Wei, Pengfei & Broggi, Matteo & Beer, Michael, 2021. "Efficient reliability analysis of complex systems in consideration of imprecision," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
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- Liu, Jintao & Chen, Keyi & Duan, Huayu & Li, Chenling, 2024. "A knowledge graph-based hazard prediction approach for preventing railway operational accidents," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
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Keywords
Multi-State System (MSS); Fuzzy Decision Tree; Multi-Valued Decision Diagram; Epistemic uncertainty; Availability; Importance measures;All these keywords.
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