影响因子：5.2
DOI码：10.1016/j.envsoft.2020.104954
发表刊物：Environmental Modelling and Software
刊物所在地：英国
关键字：Sensitivity analysis; Mathematical modeling; Machine learning; Uncertainty quantification; Decision making; Model validation and verification; Model robustness; Policy support
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.
备注：本人为第19作者（非第一作者）；全文共26位作者
论文类型：立场论文(Position Paper)
论文编号：104954
文献类型：期刊论文
卷号：137
ISSN号：1364-8152
是否译文：否
发表时间：2020-12-15
合写作者：Anthony Jakeman, Andrea Saltelli, Clémentine Prieur, Bertrand Iooss, Emanuele Borgonovo, Elmar Plischke, Samuele Lo Piano, Takuya Iwanaga, William Becker, Stefano Tarantola, Joseph H.A. Guillaume, John Jakeman, Hoshin Gupta, Nicola Melillo, Giovanni Rabitti, Vincent Chabridon, Qingyun Duan,孙熙甫, Stefán Smith, Razi Sheikholeslami, Nasim Hosseini, Masoud Asadzadeh, Arnald Puy, Sergei Kucherenko, Holger R. Maier
第一作者：Saman Razavi
通讯作者：Saman Razavi