Redes neuronales artificiales en la aplicación del crecimiento de la mancha urbana

Palabras clave: Redes Neuronales Artificiales, Autómatas Celulares, Crecimiento urbano vertical

Resumen

El objetivo de este trabajo es el uso de redes neuronales artificiales y autómatas celulares que apoyen las decisiones de planeación urbana en México. Proponemos modelo automatizado que predice el crecimiento urbano vertical, utilizando factores socioeconómicos y geográficos. Se presenta un modelo multidisciplinario que maneja redes neuronales artificiales, autómatas celulares, métodos de análisis espacial, procesamiento de imágenes que permiten proyectar y simular diferentes escenarios de crecimiento urbano. Todo esto está integrado en QGIS a través del lenguaje de programación Python. El modelo se prueba en ciudades mexicanas como Ciudad de México, Guadalajara y Monterrey durante los años 2015-2020. Se obtuvieron rangos de confiabilidad de 72% a 76%, validados por: i) el número promedio de rascacielos proyectados, ii) Posición usando el índice Kappa, y iii) Valor en la imagen usando el índice Jaccard. Con esto proponemos una técnica que permite tomar decisiones mejor informadas para la planificación urbana y anticipar nuevas necesidades de infraestructura, proyecciones y normativas.

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Publicado
2023-07-05
Cómo citar
Jiménez-López, E., & López-Rivera, L. A. (2023). Redes neuronales artificiales en la aplicación del crecimiento de la mancha urbana. Pädi Boletín Científico De Ciencias Básicas E Ingenierías Del ICBI, 11(21), 109-119. https://doi.org/10.29057/icbi.v11i21.10565
Tipo de manuscrito
Artículos de investigación