The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support

被引：314

作者：

Razavi, Saman ^{[1
]}

Jakeman, Anthony ^{[2
]}

Saltelli, Andrea ^{[3
]}

Prieur, Clementine ^{[4
]}

Iooss, Bertrand ^{[5
]}

Borgonovo, Emanuele ^{[6
]}

Plischke, Elmar ^{[7
]}

Lo Piano, Samuele ^{[8
]}

Iwanaga, Takuya ^{[2
]}

Becker, William

Tarantola, Stefano ^{[9
]}

Guillaume, Joseph H. A. ^{[2
]}

Jakeman, John ^{[10
]}

Gupta, Hoshin ^{[11
]}

Melillo, Nicola ^{[12
]}

Rabitti, Giovanni ^{[13
]}

Chabridon, Vincent ^{[5
]}

Duan, Qingyun ^{[14
]}

Sun, Xifu ^{[2
]}

Smith, Stefan ^{[8
]}

Sheikholeslami, Razi ^{[1
,15
]}

Hosseini, Nasim ^{[1
]}

Asadzadeh, Masoud ^{[16
]}

Puy, Arnald ^{[7
,17
,18
,19
]}

Kucherenko, Sergei ^{[20
]}

Maier, Holger R. ^{[21
]}

机构：

[1] Univ Saskatchewan, Global Inst Water Secur, Dept Civil Geol & Environm Engn, Sch Environm & Sustainabil, Saskatoon, SK, Canada

[2] Australian Natl Univ, Inst Water Futures, Fenner Sch Environm & Soc, Sydney, NSW, Australia

[3] Univ Oberta Catalunya UOC, Open Evidence Res, Barcelona, Spain

[4] Univ Grenoble Alpes, CNRS, INRIA, Grenoble INP,LJK, F-38000 Grenoble, France

[5] Dept PRISME, EDF R&D, Chatou, France

[6] SINCLAIR AI Lab, Saclay, France

[7] Bocconi Univ, Dept Decis Sci, I-20136 Milan, Italy

[8] Tech Univ Clausthal, Inst Disposal Res, Clausthal Zellerfeld, Germany

[9] Univ Reading, Sch Built Environm, Reading, Berks, England

[10] Joint Res Ctr JRC, European Commiss, Ispra, Italy

[11] Sandia Natl Labs, Optimizat & Uncertainty Quantificat, POB 5800, Albuquerque, NM 87185 USA

[12] Univ Arizona, Dept Hydrol & Atmospher Sci, Tucson, AZ 85721 USA

[13] Univ Pavia, Dept Elect Comp & Biomed Engn, Pavia, Italy

[14] Heriot Watt Univ, Maxwell Inst Math Sci, Dept Actuarial Math & Stat, Edinburgh, Midlothian, Scotland

[15] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China

[16] Univ Oxford, Sch Geog & Environm, Environm Change Inst, South Parks Rd, Oxford OX1 3QY, England

[17] Univ Manitoba, Dept Civil Engn, Winnipeg, MB, Canada

[18] Princeton Univ, Dept Ecol & Evolutionary Biol, M31 Guyot Hall, Princeton, NJ 08544 USA

[19] Univ Bergen, Ctr Study Sci & Humanities, Parkveien 9, N-5020 Bergen, Norway

[20] Imperial Coll London, Dept Chem Engn, London, England

[21] Univ Adelaide, Sch Civil Environm & Min Engn, Adelaide, SA, Australia

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2021年 / 137卷

基金：

澳大利亚研究理事会; 美国国家科学基金会;

关键词：

Sensitivity analysis; Mathematical modeling; Machine learning; Uncertainty quantification; Decision making; Model validation and verification; Model robustness; Policy support; MULTICRITERIA DECISION-ANALYSIS; GLOBAL SENSITIVITY; NEURAL-NETWORKS; POLYNOMIAL CHAOS; SOBOL INDEXES; UNCERTAINTY ANALYSIS; DEEP UNCERTAINTY; EVOLUTIONARY ALGORITHMS; ENVIRONMENTAL-MODELS; BAYESIAN-APPROACH;

D O I：

10.1016/j.envsoft.2020.104954

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页数：22

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