Computational Framework of Resilience
Computational Framework of Resilience
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DOI：
10.1007/978-3-319-39812-9_12
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发表时间：
2016
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影响因子：
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通讯作者：
Nicolas Schwind;Kazuhiro Minami;H. Maruyama;L. Ilmola;Katsumi Inoue
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作者：
Nicolas Schwind;Kazuhiro Minami;H. Maruyama;L. Ilmola;Katsumi Inoue
许多研究人员一直在研究城市的弹性。然而，由于涉及人类活动的系统的复杂性，很难定量定义城市地区的恢复力。我们引入了一个抽象的模型，代表了一个城市系统，通过一组变量和效用函数（或双重，成本函数）评估的“质量”的变量的状态。该成本函数取决于用于评估系统的弹性的感兴趣的标准，并且可以以简洁的方式容易地定义。因此，我们的贡献主要是两方面的。首先，我们提出了几个性能指标，评估如何弹性一个给定的系统已经在一些特定的情况下，也就是说，在过去。其次，假设我们得到了一些关于系统动态的知识，我们通过将其嵌入到离散状态转换机中来模拟其可能的演变，并展示了我们如何将性能指标适应于这个框架来预测系统未来的弹性。这种适应我们的动态模型的性能指标在这里被称为基于性能的能力指标。这种新的指标对验证现有的能力指标很有用（Ilmola在经济弹性能力指标中。城市复原力：一种变革方法。Springer，2016），将这些能力指标与我们基于绩效的指标相结合。
Many researchers have been studying the resilience in urban cities. However, due to the complexity of the system involving human activities, it is difficult to define the resilience of an urban area quantitatively. We introduce an abstract model that represents an urban system through a set of variables and a utility function (or dually, a cost function) evaluating the “quality” of the states of the variables. This cost function depends on the criterion of interest for evaluating the resilience of the system, and can be easily defined in a succinct way. Then, our contribution is mainly twofold. First, we propose several performance metrics that evaluate how resilient a given system has been in some specific scenario, that is, in the past. Second, assuming we are given some knowledge about the dynamics of the system, we model its possible evolutions by embedding it into a discrete state transition machine, and show how we can adapt the performance metrics to this framework to predict the resilience of the system in the future. Such an adaptation of a performance metric to our dynamic model is called here aperformance-based competency metric. This new kind of metric is useful to validate existing competency metrics (Ilmola in Competency metric of economic resilience. Urban resilience: a transformative approach. Springer, 2016) by aligning these competency metrics with our performance-based ones.