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Towards a Generic Framework for the Initialization and the Observation of Socio-environmental Models

机译:建立一个初始化和观察社会环境模型的通用框架

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Researchers have sought to deal with the complexity of socio-ecosystems including biophysical and social dynamics, and their interactions. In order to cope with this complexity, they need increasingly complex models, whose initialization, and observation are becoming very difficult to implement. However, no generic framework has yet been developed to address this issue. Our objective is a generic framework for specifying and implementing the initialization from numerous heterogeneous data, and the observation producing the desired indicators. The contribution of the paper is the formulation of the initialization and observation as transformations among data and data structures. This formulation allows to use the Model Driven Engineering concepts in order to implement the generic framework and the corresponding domain specific languages. The expected result will be a set of domain specific languages and their tools for specifying and automatizing the whole model exploration process from the initialization to the production of the indicators.
机译:研究人员试图应对社会生态系统的复杂性,包括生物物理和社会动态及其相互作用。为了应付这种复杂性,他们需要越来越复杂的模型,这些模型的初始化和观察变得非常困难。但是,尚未开发出通用框架来解决此问题。我们的目标是一个通用的框架,用于指定和实现来自众多异构数据的初始化,并通过观察产生所需的指标。本文的贡献是将初始化和观察公式化为数据和数据结构之间的转换。这种表述允许使用模型驱动工程概念,以实现通用框架和相应的领域特定语言。预期的结果将是一组领域特定的语言及其工具,这些工具用于指定和自动执行从初始化到指标生成的整个模型探索过程。

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