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An empirical workflow to integrate uncertainty and sensitivity analysis to evaluate agent-based simulation outputs
Environmental Modelling & Software ( IF 4.8 ) Pub Date : 2018-06-18 , DOI: 10.1016/j.envsoft.2018.06.013
Carolina G. Abreu , Celia G. Ralha

This paper presents an empirical study comparing different uncertainty analysis (UA) and sensitivity analysis (SA) methods, focussing their usefulness for the output analysis of land use/land cover change (LUCC) agent-based models (ABMs). As a result, a workflow to integrate UA and SA is presented to evaluate ABMs outputs. We developed a baseline scenario and performed a comprehensive investigation of the impacts that differences in sample sizes, sample techniques, and SA methods may have on the model output. The analysis is done in the context of a particular agent-based simulator with a LUCC model in a Brazilian Cerrado case study. The experiments indicate that there are known challenges to be overcome by the use of statistical methods. Even though the presented analysis was done over a particular simulator, we intend to contribute to the community that understands the importance of statistical validation techniques to improve the level of confidence in agent-based simulation outputs.



中文翻译:

集成不确定性和敏感性分析以评估基于代理的模拟输出的经验工作流

本文提供了一项实证研究,比较了不同的不确定性分析(UA)和敏感性分析(SA)方法,重点介绍了它们在基于土地使用/土地覆被变化(LUCC)主体模型(ABMs)的输出分析中的有用性。结果,提出了整合UA和SA的工作流程以评估ABM的输出。我们制定了基线方案,并对样本量,样本技术和SA方法的差异可能对模型输出产生的影响进行了全面调查。在巴西Cerrado案例研究中,在具有LUCC模型的特定基于代理的模拟器的背景下进行了分析。实验表明,使用统计方法可以克服已知的挑战。即使提出的分析是在特定的模拟器上完成的,

更新日期:2018-06-18
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