The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Uncertainty quantification using evidence theory in multidisciplinary design optimization
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Citations
Cites
Fuzzy Set Theory and Its Applications
Zwick, R., & Zimmermann, H.-J. (1993) · The American Journal of Psychology · doi:10.2307/1423177 · Cited by 2,921
Statistical Reasoning with Imprecise Probabilities
Walley, P. (1991) · Springer eBooks · doi:10.1007/978-1-4899-3472-7 · Cited by 2,655
Statistical Reasoning With Imprecise Probabilities
Wasserman, L., & Walley, P. (1993) · Journal of the American Statistical Association · doi:10.2307/2290362 · Cited by 2,649
Possibility theory: An approach to computerized processing of uncertainty
Tzvieli, A. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199003)41:2<153::aid-asi16>3.0.co;2-u · Cited by 2,119
Combination of Evidence in Dempster-Shafer Theory
SENTZ, K., & FERSON, S. (2002) · doi:10.2172/800792 · Cited by 1,093
Advances in the Dempster-Shafer theory of evidence
Yager, R. R., Kacprzyk, J., & Fedrizzi, M. (1994) · Iris (University of Trento) · Cited by 1,028
Reliability analysis—a review and some perspectives
Rackwitz, R. (2001) · Structural Safety · doi:10.1016/s0167-4730(02)00009-7 · Cited by 777
Fuzzy set theory- and its applications
(1991) · European Journal of Operational Research · doi:10.1016/0377-2217(91)90350-5 · Cited by 718
Hybrid Analysis Method for Reliability-Based Design Optimization
Youn, B. D., Choi, K. K., & Park, Y. H. (2003) · Journal of Mechanical Design · doi:10.1115/1.1561042 · Cited by 611
Challenge problems: uncertainty in system response given uncertain parameters
Oberkampf, W. L., Helton, J. C., Joslyn, C., Wojtkiewicz, S. F., & Ferson, S. A. (2004) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2004.03.002 · Cited by 570
Cited by
Quantification of uncertainty modelling in stochastic analysis of FRP composites
Sriramula, S., & Chryssanthopoulos, M. K. (2009) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2009.08.020 · Cited by 318
Shahriar, A., Sadiq, R., & Tesfamariam, S. (2012) · Journal of Loss Prevention in the Process Industries · doi:10.1016/j.jlp.2011.12.007 · Cited by 306
Recent advances in engineering design optimisation: Challenges and future trends
Roy, R., Hinduja, S., & Teti, R. (2008) · CIRP Annals · doi:10.1016/j.cirp.2008.09.007 · Cited by 248
Basic Framework and Main Methods of Uncertainty Quantification
Zhang, J., Yin, J., & Wang, R. (2020) · Mathematical Problems in Engineering · doi:10.1155/2020/6068203 · Cited by 52
Metadata
- Authors
- Agarwal, H., Renaud, J. E., Preston, E. L., & Padmanabhan, D.
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2004-07
- Volume
- 85
- Issue
- 1-3
- Pages
- 281-294
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W2011541053
- Cited by
- 324
- References
- 11
- FWCI
- 6.52
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Agarwal, H., Renaud, J. E., Preston, E. L., & Padmanabhan, D. (2004). Uncertainty quantification using evidence theory in multidisciplinary design optimization. Reliability Engineering & System Safety. https://doi.org/10.1016/j.ress.2004.03.017
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
