Real-time RSET prediction across three types of geometries and simulation training dataset: A comparative study of machine learning models

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F24%3APU151380" target="_blank" >RIV/00216305:26110/24:PU151380 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S266616592400142X?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S266616592400142X?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.dibe.2024.100461" target="_blank" >10.1016/j.dibe.2024.100461</a>

Result language
angličtina
Original language name
Real-time RSET prediction across three types of geometries and simulation training dataset: A comparative study of machine learning models
Original language description
Agent-based evacuation models provide useful data of the evacuation process, but they are not primarily designed for use during an emergency. The paper aims to test predicting RSET using a surrogate ML model trained on a simulation dataset with 60 samples. A total of 9 machine learning algorithms were tested on 3 simple geometries: bottleneck, stairway and walkway. A set of 7 spatial features was used to train the surrogate models. The results showed a relatively good ability of Artificial Neural Network to learn in scenarios involving bottlenecks and stairways, with an R2: 0.99 on the testing dataset. In the walkway scenario, all models experienced a significant drop in performance, with Gradient Boost performing the best (R2: 0.92). The paper demonstrated ability to generalize effectively in bottleneck-type tasks with training on a relatively small dataset containing spatial parameters obtainable in real-time from camera systems.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20101 - Civil engineering

Project
<a href="/en/project/CK02000118" target="_blank" >CK02000118: Digital Twin for Transportation - Evropska street</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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