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Crowd simulation-based knowledge mining supporting building evacuation design

机译:基于人群模拟的知识挖掘支持建筑物疏散设计

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Assessing building evacuation performance designs in emergency situations requires complex scenarios which need to be prepared and analysed using crowd simulation tools, requiring significant manual input. With current procedures, every design iteration requires several simulation scenarios, leading to a complicated and time-consuming process. This study aims to investigate the level of integration between digital building models and crowd simulation, within the scope of design automation. A methodology is presented in which existing ontology tools facilitate knowledge representation and mining throughout the process. Several information models are used to integrate, automate and provide feedback to the design decision-making processes. The proposed concept thus reduces the effort required to create valid simulation scenarios by applying represented knowledge, and provides feedback based on results and design objectives. To apply and test the methodology a system was developed, which is introduced here. The context of building performance during evacuation scenarios is considered, but additional design perspectives can be included. The system development section expands on the essential theoretical concepts required and the case study section shows a practical implementation of the system.
机译:在紧急情况下评估建筑物疏散性能设计需要复杂的场景,需要使用人群模拟工具进行准备和分析,需要大量的人工输入。使用当前的程序,每次设计迭代都需要几种仿真方案,从而导致复杂而耗时的过程。这项研究的目的是在设计自动化范围内研究数字建筑模型与人群模拟之间的集成水平。提出了一种方法,其中现有的本体工具可促进整个过程中的知识表示和挖掘。几个信息模型用于集成,自动化设计决策过程并向其提供反馈。因此,提出的概念通过应用代表的知识减少了创建有效的模拟方案所需的工作,并基于结果和设计目标提供了反馈。为了应用和测试该方法,开发了一个系统,此处介绍。考虑了疏散场景中建筑物性能的背景,但是可以包括其他设计观点。系统开发部分扩展了所需的基本理论概念,案例研究部分显示了该系统的实际实现。

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