Abstract

Risk assessment is an important and significant aid in the decision making process. Risk assessment is performed using ‘model’ and a model is a function of parameters which are usually affected by uncertainty. Some model parameters are affected by aleatory uncertainty and some others are affected by epistemic uncertainty. In this paper we propose a hybrid method to deal with propagation of both kinds of uncertainty within the same computation of risk.

References

• A. Bardossy, A. Bronstert A, B Merz , 1-, 2- and 3-dimensional modelling of groundwater movement in the unsaturated soil matrix using a fuzzy approach, Adv. Water Resources, 18 (1995) 237–251.
• C Baudrit, D. Dubois, H. Fargier, Propagation of Uncertainty involving Imprecision and Randomness. Proc.3d European Conference on Fuzzy Logic and Technology, Zittau (Germany), (2003) 653-658.
• C. Baudrit, D. Dubois, H. Fargier, Joint treatment of imprecision and randomness in uncertainty propagation, In:Modern Information Processing: From Theory to Applications. B. Bouchon-Meunier, G. Coletti, R.R. Yager (Eds.), Elsevier, (2006) 37-47.
• C. Baudrit, D. Dubois, Comparing Methods for Joint Objective and Subjective Uncertainty Propagation with an example in a risk assessment, Fourth International Symposium on Imprecise Probabilities and Their Application (ISIPTA’05), Pittsburg (USA, Pennsylvanie), (2005) 31-40.
• C. Baudrit, D. Dubois, D. Guyonnet, H. Fargier, Joint Treatment of imprecision and Randomness in Uncertainty Propagation, Proc. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Perugia, (2004) 873-880.
• C. Baudrit, D. Dubois, D. Guyonnet, Joint Propagation and Exploitation of Probabilistic and Possibilistic Information in Risk Assessment, IEEE Transaction on Fuzzy Systems, 14 (2006) 593-608.
• C. Dou, W. Woldt, I. Bogardi, M. Dahab, Steady-state groundwater flow simulation with imprecise parameters, Water Resource Res., 31 (1995) 2709–2719.
• D. Guyonnet, B. Bourgine, D. Dubois, H. Fargier, B. Côme, J. P. Chilès, Hybrid approach for addressing uncertainty in risk assessments, Journal of Environmental Engineering, 126 (2003) 68-78.
• D. Guyonnet, B. Côme, P. Perrochet, A. Parriaux, Comparing two methods for addressing uncertainty in risk assessments, Journal of Environmental Engineering, 125(1999) 660-666.
• E.Kentel, M. M. Aral, Probalistic-fuzzy health risk modeling, Stoch Envir Res and Risk Ass 18(2004) 324-338.
• EPA US. 2001. Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment). Office of Emergency and Remedial Response, EPA/540/R/99/005, Interim, Review Draft. United States Environmental Protection Agency. September 2001.
• H. W. Ma, K. Y. Wu, C. D. Ton, Setting information priorities for remediation decisions at a contaminated-groundwater site, Chemosphere 46 (2002) 75–81.
• H. W. Ma, Stochastic multimedia risk assessment for a site with contaminated groundwater, Stochastic Environ Res Risk Assess 16 (2002) 464–478.
• K. Ganesan, P. Veeramani, on Arithmetic operations of interval numbers, International journal of uncertainly and knowledge based systems, 13 (2005) 619-631.
• P. Labieniec , D. Dzombak, R. Siegrist, Evaluation of uncertainty in a site-specific risk assessment, J. Environ. Eng., 123(1997) 234–243.
• P. Prado D. Draper, S. Saltelli, A. Pereira, B. Mendes, S. Eguilior, R. Cheal, S. Tarantola, Gesamac: Conceptual and computational tools to tackle the long-term risk from nuclear waste disposal in the geosphere, in Eur. Commission Rep. EUR 19113 EN: Office for Official Publications of the European Communities, Luxemburg, 1999, vol. 87.
• R. M. Maxwell, S.D. Pelmulder, A. F. B. Tompson, W. E. Kastenberg, On the development of a new methodology for groundwater-driven health risk assessment, Water Resources Res, 34(1998) 833–847.
• R. M. Maxwell, W. E. Kastenberg, Stochastic environmental risk analysis: an integrated methodology for predicting cancer risk from contaminated groundwater, Stochastic Environ Res Risk Assess 13 (1999) 27–47.