Open Access
Numéro |
Radioprotection
Volume 55, May 2020
Coping with uncertainties for improved modelling and decision making in nuclear emergencies. Key results of the CONFIDENCE European research project
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Page(s) | S175 - S180 | |
Section | DECISION MAKING UNDER UNCERTAINTIES | |
DOI | https://doi.org/10.1051/radiopro/2020029 | |
Publié en ligne | 20 mai 2020 |
- Almahayni T, Sweeck L, Beresford NA, Barnett CL, Lofts S, Hosseini A, Brown J, Thørring H, Guillén J. 2019. An evaluation of process-based models and their application in food chain assessments. CONCERT Deliverable D9.15. Available from https://concert-h2020.eu/en/Publications. [Google Scholar]
- Banks DL, Aliaga JMR, Insua DR. 2015. Adversarial risk analysis. Boca Raton: CRC Press. [CrossRef] [Google Scholar]
- Barberis NC. 2013. Thirty years of prospect theory in economics: A review and assessment. J Econ Perspect 27(1): 173–196. [Google Scholar]
- Barnett V. 1999. Comparative statistical inference. Chichester: John Wiley and Sons. [CrossRef] [Google Scholar]
- Beresford NA, Barnett CL, Chaplow J, Lofts S, Wells C, Brown JE, Hosseini A, Thørring H, Almahayni T, Sweeck L, Guillén J, Lind O-C, Oughton DH, Salbu B, Teien H-C, Perez-Sánchez D, Real A. 2020. CONFIDENCE Overview of improvements in radioecological human food chain models and future needs. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020019. [Google Scholar]
- Berkeley D, Humphreys PC. 1982. Structuring decision problems and the “bias heuristic”. Psychol. Bull. 50: 201–252. [Google Scholar]
- Charron S. et al. 2016. Overview of the PREPARE WP3: Management of contaminated goods in post-accidental situation – Synthesis of European stakeholders’ panels. Radioprotection 51(HS2): S83–S91. [EDP Sciences] [Google Scholar]
- Comes T, Hiete M, Wijngaards N, Schultmann F. 2011. Decision maps: A framework for multi-criteria decision support under severe uncertainty. Decis. Support Syst. 52(1): 108–118. [Google Scholar]
- Conti S, Gosling JP, Oakley JE, O’hagan A. 2009. Gaussian process emulation of dynamic computer codes. Biometrika 96(3): 663–676. [Google Scholar]
- Craig PS, Goldstein M, Rougier JC, Seheult AH. 2001. Bayesian forecasting for complex systems using computer simulators. J. Am. Stat. Assoc. 96(454): 717–729. [Google Scholar]
- Draper D. 1995. Assessment and propagation of model uncertainty (with discussion). J. R. Stati. Soc. B57(1): 45–97. [Google Scholar]
- Duranova T, Raskob W, Beresford NA, Korsakissok I, Montero M, Müller T, Turcanu C, Woda C. 2020a. CONFIDENCE dissemination meeting: Summary on the scenario based workshop. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020009. [Google Scholar]
- Duranova T, van Asselt E, Müller T, Bohunova J, Twenhöfel CJW, Smetsers. 2020b. MCDA stakeholder workshops. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020032. [Google Scholar]
- Eden C, Ackermann F. 1998. Making strategy: The journey of strategic management. London: Sage. [Google Scholar]
- Evans JR, Olson DL. 2002. Introduction to simulation and risk analysis. Upper Saddle River, NJ: Prentice Hall. [Google Scholar]
- French S. 1995. Uncertainty and imprecision: Modelling and analysis. J. Oper. Res. Soc. 46(1): 70–79. [Google Scholar]
- French S. 1997. Uncertainty modelling, data assimilation and decision support for management of off-site nuclear emergencies. Radiat. Prot. Dosim. 73: 11–15. [CrossRef] [Google Scholar]
- French S. 2003. Modelling, making inferences and making decisions: The roles of sensitivity analysis. TOP 11(2): 229–252. [CrossRef] [MathSciNet] [Google Scholar]
- French S. 2015. Cynefin: Uncertainty, small worlds and scenarios. J. Oper. Res. Soc. 66(10): 1635–1645. [Google Scholar]
- French S, Rios Insua D. 2000. Statistical decision theory. London: Arnold. [Google Scholar]
- French S, Maule AJ, Papamichail KN. 2009. Decision behaviour, analysis and support. Cambridge: Cambridge University Press. [CrossRef] [Google Scholar]
- French S, Argyris N, Layton H, Smith JQ, Haywood SM, Hort M. 2016. Presenting uncertain information in radiological emergencies. Available from https://admlc.wordpress.com/publications/. UK Atmospheric Dispersion Modelling Liaison Committee. [Google Scholar]
- French S, Argyris N, Haywood S, Hort M, Smith J. 2017. Uncertainty handling during nuclear accidents. ISCRAM2017. Albi: ISCRAM. Available from www.iscram.org. [Google Scholar]
- Galmarini S, Bianconi R, De Vries G, Bellasio R. 2008. Real-time monitoring data for real-time multi-model validation: Coupling ENSEMBLE and EURDEP. J. Environ. Radioact. 99(8): 1233–1241. [CrossRef] [PubMed] [Google Scholar]
- Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB. 2013. Bayesian data analysis. London: Chapman and Hall. [CrossRef] [Google Scholar]
- Goldstein M. 2011. External Bayesian analysis for computer simulators (with discussion). Bayesian Statistics 9 (JM Bernardo et al., Eds.). Oxford: Oxford University Press (in press). [Google Scholar]
- Goldstein M, Rougier JC. 2009. Reified Bayesian Modelling and inference for physical systems (with discussion). J. Stat.l Plan. Inference 139: 1221–1256. [CrossRef] [Google Scholar]
- Hamburger T, Gering F, Ievdin I, Schantz S, Geertsema G, de Vries H. 2020. Uncertainty propagation from ensemble dispersion simulations through a terrestrial food chain and dose model. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020014. [Google Scholar]
- Haywood SM. 2010. A method for displaying imprecision in early radiological emergency assessments. J. Radiol. Prot. 30(4): 673. [Google Scholar]
- Haywood SM, Bedwell P, Hort M. 2010. Key factors in imprecision in radiological emergency response assessments using the NAME model. J. Radiol. Prot. 30(1): 23–36. [Google Scholar]
- Hennig P, Osborne MA, Girolami M. 2015. Probabilistic numerics and uncertainty in computations. London: Proc. R. Soc. A, The Royal Society. [Google Scholar]
- Hiete M, Bertsch V, Comes T, Schultmann F, Raskob W. 2010. Evaluation strategies for nuclear and radiological emergency and post-accident management. Radioprotection 45(5): S133–S147. [CrossRef] [EDP Sciences] [Google Scholar]
- Howard BJ, Liland A, Beresford NA, Anderson K, Crout NMJ, Gil JM, Hunt J, Nisbet A, Oughton DH, Voight G. 2005. The STRATEGY Project: Decision tools to aid sustainable restoration and long-term management of contaminated agricultural ecosystems. J. Environ. Radioact. 83: 275–296. [CrossRef] [PubMed] [Google Scholar]
- Kacprzyk J, Zadrozny S. 2010. Computing with words is an implementable paradigm: Fuzzy queries, linguistic data summaries, and natural-language generation. IEEE Trans. Fuzzy Syst. 18(3): 461–472. [Google Scholar]
- Kahneman D, Tversky A. 1979. Prospect theory: An analysis of decisions under risk. Econmetrica 47: 263–291. [CrossRef] [MathSciNet] [Google Scholar]
- Keeney RL. 1992. Value-focused thinking: A path to creative decision making. Cambridge, MA: Harvard University Press. [Google Scholar]
- Keil AP, Richardson DB. 2018. Quantifying cancer risk from radiation. Risk Anal. 38(7): 1474–1489. [PubMed] [Google Scholar]
- Kuhn TS. 1961. The function of measurement in modern physical science. Isis 52(2): 161–193. [Google Scholar]
- Mathieu A, Korsakissok I, Périllat R, Chevalier-Jabet K, Stephani F, Fougerolle S, Créach V, Cogez E, Bedwell P. 2018a. Guidelines ranking uncertainties for atmospheric dispersion, D9.1.3 Guidelines describing source term uncertainties. CONCERT Deliverable D9.1. Available from https://concert-h2020.eu/en/Publications. [Google Scholar]
- Mathieu A, Korsakissok I, Andronopoulos S, Bedwell P, Chevalier-Jabet K, Cogez E, Créach V, Fougerolle S, Geertsema G, Gering F, Hamburger T, Jones AR, Klein H, Leadbetter S, Pázmándi T, Périllat R, Rudas C, Sogachev A, Stephani F, Szanto P, Tomas J, Twenhöfel C, de Vries H, Wellings J. 2018b. Guidelines ranking uncertainties for atmospheric dispersion. CONCERT Deliverable D9.1. Available from https://concert-h2020.eu/en/Publications. [Google Scholar]
- Mercer J. 2005. Prospect theory and political science. Ann. Rev. Polit. Sci. 8: 1–21. [CrossRef] [Google Scholar]
- Nagy A, Perko T, Müller T, Raskob W, Benighaus L. 2020. Uncertainty visualization using maps for nuclear and radiological emergencies. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020033. [Google Scholar]
- Nisbet AF et al. 2005. Achievements, difficulties and future challenges for the FARMING network. J. Environ. Radioact. 83(3): 263–274. [Google Scholar]
- Nisbet A et al. 2010. Decision aiding handbooks for managing contaminated food production systems, drinking water and inhabited areas in Europe. Radioprotection 45(5 Supplement): S23–S37. [CrossRef] [EDP Sciences] [Google Scholar]
- O’Brian FA, Dyson RG (Eds.) 2007. Supporting strategy: Frameworks, methods and models. Chichester: John Wiley and Sons, Ltd. [Google Scholar]
- O’Hagan A. 2006. Bayesian analysis of computer code outputs: A tutorial. Reliab. Eng. Syst. Saf. 91(10): 1290–1300. [CrossRef] [Google Scholar]
- O’Hagan A. 2012. Probabilistic uncertainty specification: Overview, elaboration techniques and their application to a mechanistic model of carbon flux. Environ. Model. Softw. 36: 35–48. [Google Scholar]
- Oughton DH, Bay I, Forsberg E-M, Kaiser M, Howard B. 2004. An ethical dimension to sustainable resoration and long-term management of contaminated areas. J. Environ. Radioact. 74: 171–183. [CrossRef] [PubMed] [Google Scholar]
- Perko T, Tafili V, Sala R, Duranova T, Zeleznik N, Tomkiv Y, Hoti F, Turcanu C. 2019. Report on observational study of emergency exercises: List of uncertainties. CONCERT Deliverable D9.28. Available from https://www.concert-h2020.eu/en/Publications. [Google Scholar]
- Phillips LD. 1984. A theory of requisite decision models. Acta Psychol. 56(1–3): 29–48. [CrossRef] [Google Scholar]
- Saltelli A, Chan K, Scott EM (Eds.) 2000a. Sensitivity analysis. Chichester: John Wiley and Sons. [Google Scholar]
- Saltelli A, Tarantola S, Campolongo F. 2000b. Sensitivity analysis as an ingredient of modelling. Stat. Sci. 15(4): 377–395. [Google Scholar]
- Saltelli A, Tarantola S, Campolongo F, Ratto M. 2004. Sensitivity analysis in practice: A guide to assessing scientific models. Chichester: John Wiley and Sons. [Google Scholar]
- Snowden D. 2002. Complex acts of knowing – Paradox and descriptive self-awareness. J. Knowl. Manag. 6(2): 100–111. [CrossRef] [Google Scholar]
- Tomkiv Y, Perko T, Sala R, Zeleznik N, Maitre M, Schneider T, Oughton DH. 2020. Societal uncertainties recognised in recent nuclear and radiological emergencies in Europe. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020025. [Google Scholar]
- Turcanu C, Perko T, Wolf HV, Camps J, Oughton DH. 2020a. Social uncertainties associated with stable iodine intake in a nuclear emergency. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020027. [Google Scholar]
- Turcanu C, Perko T, Baudé S, Hériard-Dubreuil G, Zeleznik N, Oughton DH, Tomkiv Y, Sala R, Oltra C, Tafili V, Benighaus L, Maitre M, Schneider T, Crouail P, Duranova T, Paiva I. 2020b. Social, ethical and communication aspects of uncertainty management. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020024. [Google Scholar]
- Walker WE et al. 2003. Defining uncertainty: A conceptual basis for uncertainty management in model-based decision support. Integr. Assess. 4(1): 5–17. [CrossRef] [Google Scholar]
- Walsh L, Ulanowski A, Kaiser JC, Woda C, Raskob W. 2019. Risk bases can complement dose bases for implementing and optimizing a radiological protection strategy in urgent and transition emergency phases. Radiat. Environ. Biophys. 58: 539–552. [CrossRef] [PubMed] [Google Scholar]
- Wellings J, Bedwell P, Leadbetter S, Tomas J, Andronopoulos S, Korsakissok I, Périllat R, Mathieu A, Geertsema G, De Vries H, Klein H, Hamburger T, Gering F, Pázmándi T, Szántó P, Rudas C, Sogachev A, Davis N, Twenhöfel C. 2018. Guidelines ranking uncertainties for atmospheric dispersion, D9.1.5 Guidelines for ranking uncertainties in atmospheric dispersion. CONCERT Deliverable D9.1. Available from https://concert-h2020.eu/en/Publications. [Google Scholar]
- Zeleznik N, Benighaus L, Mitrakos D, Tafili V, Duranova T, Sala R, Benighaus C. 2020. Mental models of uncertainty management in nuclear emergency management. Radioprotection 55(HS1). https://doi.org/10.1051/radiopro/2020026. [Google Scholar]
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