Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 171, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2023.105898
Keywords
Global sensitivity analysis; Simulation decomposition; Monte Carlo simulation; Decision-making under uncertainty
Ask authors/readers for more resources
This paper introduces a framework for quantitative sensitivity analysis using the SimDec visualization method, and tests its effectiveness on decision-making problems. The framework captures critical information in the presence of heterogeneous effects, and enhances its practicality by introducing a formal definition and classification of heterogeneous effects.
Computational modeling is frequently incorporated into environmental decision-making in order to capture inherently complex relationships and system dynamics. The complexity of such models often lies in various heterogeneous effects that arise due to the interaction of different input factors or due to designed structural variation in the model. In the past, various sensitivity analysis approaches have been implemented in attempts to identify essential decision factors. However, existing sensitivity analysis methods fail to capture critical information in the presence of heterogeneous effects. In this paper, the recently introduced simulation decomposition (SimDec) visualization method is extended to include quantitative sensitivity analysis. The framework is tested on several decision-making problems and is shown to capture heterogeneous behavior. A formal definition and classification of heterogeneous effects for computational models is introduced. The framework is open-sourced in a variety of scientific programming languages.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available