Previsão do tempo de evacuação e recomendação de estratégias de resgate em cenários de evacuação horizontal com evacuadores enfraquecidos

• Raimundo Juracy Campos Ferro Junior UECE
• Gustavo Augusto Lima de Campos UECE

DOI: https://doi.org/10.5753/eniac.2022.227591

Abstract

One of the challenges in the context of studying evacuation processes and rescue situations is the lack of studies and tools that address dependent evacuees or the possibility of simulating different rescue strategies. This work aims to fill this gap. Proposing an agent-based architecture that can produce data, train regression algorithms to make predictions about horizontal evacuation scenarios with dependent evacuees, and propose rescue strategies. The decision tree and multilayer perceptron network algorithms presented the best result for the regression of the evacuation time and the random-forest model was able to reach an accuracy of 92% when classifying the scenarios based on the most appropriate strategy for the rescue team.

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