Open Access
Issue
JNWPU
Volume 40, Number 2, April 2022
Page(s) 450 - 457
DOI https://doi.org/10.1051/jnwpu/20224020450
Published online 03 June 2022
  1. GUO Shuxiang, LYU Zhenzhou. Comparison between the non-probabilistic and probabilistic reliability method for uncertain structure design[J]. Chinese Joural of Applied Mechanic, 2003, 20(3): 107–110 [Article] (in Chinese) [NASA ADS] [Google Scholar]
  2. BAUDRIT C, DUBOIS D. Practical representations of incomplete probabilistic knowledge. The fuzzy approach to statistical analysis[J]. Computational Statistical & Data Analysis, 2006, 51(1): 86–108 [CrossRef] [Google Scholar]
  3. FERSON S, KREINOVICH V, HAJAGOS J, et al. Experimental uncertainty estimation and statistics for data having interval uncertainty[R]. SAND-2007-0939 [Google Scholar]
  4. FERSON S, TUCKER W T. Sensitivity in risk analyses with uncertain numbers[R]. SAND-2006-2801 [Google Scholar]
  5. ZAMAN K, RANGAVAJHALA S, MCDONALD M P, et al. A probabilistic approach for representation of interval uncertainty[J]. Reliability Engineering and System Safety, 2011, 96: 117–130 [Article] [CrossRef] [Google Scholar]
  6. WILLIAMSON R C. Probabilistic arithmetic[D]. Brisbane: University of Queensland, 1989 [Google Scholar]
  7. MONTGOMERY V. New statistical methods in risk assessment by probability bounds[D]. Durham: Durham University, 2009 [Google Scholar]
  8. SANKARARAMAN S, MAHADEVAN S. Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data[J]. Reliability Engineering and System Safety, 2011, 96: 814–824 [Article] [CrossRef] [Google Scholar]
  9. ELISHAKOFF I, COLOMBI P. Combination of probabilistic and convex models of uncertainty when scare knowledge is present on acoustic excitation on parameters[J]. Computer Methods in Applied Mechanics and Engineering, 1993, 104: 187–209 [Article] [CrossRef] [Google Scholar]
  10. CAO Hongjun, DUAN Baoyan. An approach on the non-probabilitic reliability of structures based on uncertainty convex models[J]. Chinese Joural of Computational Mechanics, 2005, 22(5): 546–549 [Article] (in Chinese) [NASA ADS] [Google Scholar]
  11. QIU Z P, YANG D, ELISHAKOFF I. Probabilistic interval reliability of structural systems[J]. International Journal of Solids and Structures, 2008, 45: 2850–2860 [Article] [CrossRef] [Google Scholar]
  12. SOIZE C. Maximum entropy approach for modeling random uncertainties in transient elastodynamics[J]. Journal of Acoustical Society of America, 2001, 109(5): 1979–1996 [Article] [NASA ADS] [CrossRef] [Google Scholar]
  13. LYU Zhenzhou, SONG Shufang, LI Hongshuang, et al. Reliability and reliability sensitivity analysis of uncertainty structure[M]. Beijing: Science Press, 2009 (in Chinese) [Google Scholar]
  14. ZHAO Yu. Data analysis of reliability[M]. Beijing: Beihang University Press, 2011 (in Chinese) [Google Scholar]
  15. REZA F M. An introduction to information theory[M]. New York: Dover Publications, 1994 [Google Scholar]
  16. SHANNON C E. A mathematical theory of communication[J]. Bell System Technical Journal, 1948, 27: 379–423 [Article] [CrossRef] [Google Scholar]
  17. SOIZE C. Maximum entropy approach for modeling random uncertainties in transient elastodynamics[J]. Journal of Acoustical Society of America, 2001, 109(5): 1979–1996 [Article] [NASA ADS] [CrossRef] [Google Scholar]
  18. GONG Chun, WANG Zhenglin. Programs collection of algorithm in common use based on Matlab[M]. Beijing: Publishing House of Electronics Industry, 2011 (in Chinese) [Google Scholar]
  19. OBERKAMPF W L, HELTON J C, JOSLYN C A, et al. Challenge problems: uncertainty in system response given uncertain parameters[J]. Reliability Engineering and System Safety, 2004, 85: 11–19 [Article] [CrossRef] [Google Scholar]
  20. FERSON S, JOSLYN C A, HELTON J C. Summary from the epistemic uncertainty workshop: consensus amid diversity[J]. Reliability Engineering and System Safety, 2004, 85: 355–369 [Article] [CrossRef] [Google Scholar]
  21. ZHANG F, XU X, WANG L, et al. Global sensitivity analysis of twostage thermoelectric refrigeration system based on response variance[J]. Intentional Journal of Energy Research, 2020, 44: 6623–6630 [Article] [CrossRef] [Google Scholar]
  22. LYU Zhenzhou, LI Luyi, SONG Shufang. Importance analysis theory and solution method of uncertain structural system[M]. Beijing: Science Press, 2016 (in Chinese) [Google Scholar]
  23. BOTEV Z I, GROTOWSKI J F, KROESE D P. Kernel density estimation via diffusion[J]. The Annals of Statistics, 2010, 38: 2916–2957 [CrossRef] [Google Scholar]
  24. BOTEV Z I. Kernel density estimation using Matlab[EB/OL]. (2015-12-30)[2020-09-19]. [Article] [Google Scholar]

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