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Título : | The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support |
Autoría: | Razavi, Saman Jakeman, Anthony Saltelli, Andrea Prieur, Clémentine Iooss, Bertrand Borgonovo, Emanuele Plischke, Elmar Lo Piano, Samuele Iwanaga, Takuya Becker, William Tarantola, Stefano Guillaume, Joseph Jakeman, John Gupta, Hoshin Melillo, Nicola Rabitti, Giovanni Chabridon, Vincent Duan, Qingyun SUN, XIFU Smith, Stefan Sheikholeslami, Razi Hosseini, Nasim Asadzadeh, Masoud Puy, Arnald Kucherenko, Sergei Maier, Holger |
Otros: | University of Saskatchewan The Australian National University Universitat Oberta de Catalunya (UOC) Université de Grenoble Alpes EDF R&D, Département PRISME / SINCLAIR AI Laboratory Bocconi University Technische Universität Clausthal University of Reading University of Arizona Università degli Studi di Pavia Heriot-Watt University Hohai University University of Oxford University of Manitoba Princeton University University of Bergen Imperial College London University of Adelaide |
Citación : | Razavi, S., Jakeman, A., Saltelli, A., Prieur, C., Iooss, B., Borgonovo, E., Plischke, E., Lo Piano, Samuele, Iwanaga, T., Becker, W., Tarantola, S., Guillaume, J., Jakeman, J., Gupta, H., Melillo, Nicola, Rabitti, G., Chabridon, V., Duan, Q., Sun, X., Smith, S., Sheikholeslami, R., Hosseini, N., Asadzadeh, M., Puy, A., Kucherenko, S. & Maier, H.R. (2021). The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support. Environmental Modelling & Software, 137, 1-22. doi: 10.1016/j.envsoft.2020.104954 |
Resumen : | Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society. |
Palabras clave : | análisis de sensibilidad modelización matemática aprendizaje automático cuantificación de la incertidumbre toma de decisiones validación y verificación de modelos robustez del modelo apoyo a la política |
DOI: | https://doi.org/10.1016/j.envsoft.2020.104954 |
Tipo de documento: | info:eu-repo/semantics/article |
Versión del documento: | info:eu-repo/semantics/publishedVersion |
Fecha de publicación : | 16-ene-2021 |
Licencia de publicación: | https://creativecommons.org/licenses/by/4.0/ |
Aparece en las colecciones: | Articles cientÍfics Articles |
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The_Future_of_Sensitivity_Analysis_An_essential_discipline_for_systems_modeling_and_policy_support.pdf | 2,52 MB | Adobe PDF | Visualizar/Abrir |
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