Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty
Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty
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DOI：
10.1016/j.techfore.2012.10.005
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发表时间：
2013-03-01
影响因子：
12
通讯作者：
Pruyt, Erik
中科院分区：
文献类型：
--
作者：
Kwakkel, Jan H.;Pruyt, Erik
探索性建模和分析（EMA）是一种使用计算实验来分析复杂和不确定问题的方法。它主要是为了基于模型的决策支持而开发的。本文研究了 EMA 在多大程度上是面向未来的技术分析 (FTA) 的一种有前景的方法。我们报告了 EMA 在三个不同技术领域使用不同建模方法的三种应用。在第一种情况下，EMA 与系统动力学 (SD) 相结合，研究矿物和金属稀缺的合理动力学。 EMA 和 SD 组合的主要目的是深入了解在各种不确定性和对系统的基本了解的情况下可能会发生什么样的令人惊讶的动态。在第二种情况下，EMA 与机场绩效计算的混合模型相结合，以制定适应性战略计划。这个案例展示了如何通过识别可能导致计划执行不佳的外部条件来迭代改进战略计划。在最后一个案例中，EMA 与基于代理的模型相结合，研究电力部门的转型动态，并确定对电力部门向更可持续运作的转型产生积极和消极影响的关键因素。本文的结论是，尽管存在大量不确定性，但 EMA 对于产生远见、研究系统性和结构性转型以及设计强有力的政策和计划（这是 FTA 的关键活动）很有用。 (C) 2012 Elsevier Inc. 保留所有权利。
Exploratory Modeling and Analysis (EMA) is an approach that uses computational experiments to analyze complex and uncertain issues. It has been developed mainly for model-based decision support. This paper investigates the extent to which EMA is a promising approach for future oriented technology analysis (FTA). We report on three applications of EMA, using different modeling approaches, in three different technical domains. In the first case, EMA is combined with System Dynamics (SD) to study plausible dynamics for mineral and metal scarcity. The main purpose of this combination of EMA and SD is to gain insight into what kinds of surprising dynamics can occur given a variety of uncertainties and a basic understanding of the system. In the second case, EMA is combined with a hybrid model for airport performance calculations to develop an adaptive strategic plan. This case shows how one can iteratively improve a strategic plan through the identification of plausible external conditions that would cause the plan to perform poorly. In the final case, EMA is combined with an agent-based model to study transition dynamics in the electricity sector and identify crucial factors that positively and negatively affect a transition towards more sustainable functioning of the electricity sector. This paper concludes that EMA is useful for generating foresights and studying systemic and structural transformations despite the presence of a plethora of uncertainties, and for designing robust policies and plans, which are key activities of FTA. (C) 2012 Elsevier Inc. All rights reserved.