Implementación de un nuevo algoritmo de clasificación en el lenguaje R.
Loading...
Official URL
Full text at PDC
Publication date
2022
Authors
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Citation
Abstract
En los últimos años las mejoras en infraestructura urbana que se ha realizado en Madrid Central, junto con la nueva normativa de cierre al tráfico rodado ha propiciado la afluencia de peatones, principalmente en lo meses de verano, lo que ocasiona una serie de problemas en aquellas zonas donde no se prevé aglomeraciones debido a que no están dotadas estructuralmente para ello. Por ende se propone la implementación de un nuevo algoritmo de clasificación basado en la fusión de K-MEANS y Hierarchical clustering que nos permita conocer que calles comparten un promedio de peatones similar en el periodo vacacional, así, de este modo se puede aplicar mejoras urbanas basándonos en la clasificación generada en aquellas zonas con mayor número de peatones.
Nowadays the improvements in urban infrastructure that has been made in Madrid Central, along with the new regulations for closing to road traffic has led to the influx of walkers, mainly in the summer months, which causes a number of problems in those areas where agglomerations are not expected because they are not structurally equipped for it. Therefore, we propose the implementation of a new classification algorithm based on the fusion of K-MEANS and Hierarchical clustering that allows us to know which streets share a similar average number of pedestrians in the holiday period, besides in this way we can apply urban improvements based on the classification generated in those areas with the highest number of walkers.
Nowadays the improvements in urban infrastructure that has been made in Madrid Central, along with the new regulations for closing to road traffic has led to the influx of walkers, mainly in the summer months, which causes a number of problems in those areas where agglomerations are not expected because they are not structurally equipped for it. Therefore, we propose the implementation of a new classification algorithm based on the fusion of K-MEANS and Hierarchical clustering that allows us to know which streets share a similar average number of pedestrians in the holiday period, besides in this way we can apply urban improvements based on the classification generated in those areas with the highest number of walkers.
Description
Trabajo de Fin de Grado en Ingeniería Informática, Facultad de Informática UCM, Departamento de de Sistemas Informáticos y Computación, Curso 2021/2022.