Data-driven simulation of pedestrian collision avoidance with a nonparametric neural network
"Data-driven simulation of pedestrian dynamics is an incipient and promising approach for building reliable microscopic pedestrian models. We propose a methodology based on generalized regression neural networks, which does not have to deal with a huge number of free parameters as in the case o...
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| Autores principales: | Martin, Rafael F., Parisi, Daniel |
|---|---|
| Formato: | Artículos de Publicaciones Periódicas acceptedVersion |
| Lenguaje: | Inglés |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | http://ri.itba.edu.ar/handle/123456789/2230 |
| Aporte de: |
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