期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 146, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2021.105226
关键词
Sensitivity analysis; Uncertainty analysis; Evidence based policy; Machine learning; Validation and verification of mathematical models
Sensitivity analysis as a key component of scientific development and policy support has been rapidly evolving over the past three decades. Researchers and practitioners from various disciplines have contributed to the development of sensitivity analysis, fostering a community culture through conferences. The field is now maturing into an independent science with emerging applications in new areas such as data science and machine learning.
Sensitivity analysis (SA) as a 'formal' and 'standard' component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA over the last three decades, and the SAMO (sensitivity analysis of model output) conferences, since 1995, have been the primary driver of breeding a community culture in this heterogeneous population. Now, SA is evolving into a mature and independent field of science, indeed a discipline with emerging applications extending well into new areas such as data science and machine learning. At this growth stage, the present editorial leads a special issue consisting of one Position Paper on The future of sensitivity analysis and 11 research papers on Sensitivity analysis for environmental modelling published in Environmental Modelling & Software in 2020-21.
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