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Ant Colony-Dijkstra's Algorithm for Evacuation Preparedness in High Rise Buildings

机译:蚁群-Dijkstra在高层建筑中疏散准备的算法

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The critical tasks during evacuation process is how to find the right ways in order to escape from the danger place to a safe place. In process of finding the right ways, most of the evacuees are panicked. Subsequently, make the process more difficult. With that occurrence, the main objectives of this research study are to identify the suitable shortest path algorithm for evacuation in high rise building, then design and develop an evacuation route via shortest path algorithm in order to obtain an exit route to evacuate by using Optimization and Artificial Intelligence Technique. The objectives that involved are to help the evacuees to find the best routes during evacuation process. Six phases of methods are raised to accomplish the objectives by utilizing the Dijkstra and Ant Colony Optimization Algorithm. The first step is started from the original building layout. Then transform the layout into 2D layout plan. After that, import the matrix data to generate graph theory. Next step is utilizing the both approaches to achieve the shortest path. The preliminary result has shown positive result which can deliver the shortest path to help evacuees.
机译:疏散过程中的关键任务是如何找到正确的方式,以逃离危险地点到安全的地方。在寻找正确的方式的过程中,大多数疏口都是惊慌失措的。随后,使过程更加困难。通过这种情况,本研究研究的主要目标是确定高层建筑中疏散的合适最短路径算法,然后通过最短路径算法设计和开发疏散路径,以便通过使用优化和通过优化撤离退出路线人工智能技术。所涉及的目标是帮助撤离人员在疏散过程中找到最佳路线。提高了六个阶段来实现目的,通过利用Dijkstra和蚁群优化算法来实现目标。第一步是从原始建筑布局开始的。然后将布局转换为2D布局计划。之后,导入矩阵数据以生成图形理论。下一步是利用两种方法来实现最短路径。初步结果显示了肯定的结果,可以提供最短的路径来帮助疏散。

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