Predicción de la producción de residuos con incertidumbre en la ciudad inteligente mediante neuroevolución profunda

Autores/as

DOI:

https://doi.org/10.17533/udea.redin.20190736

Palabras clave:

neuroevolución profunda, aprendizaje profundo, algoritmos evolutivos, ciudad inteligente, gestión de residuos

Resumen

El desarrollo insostenible de los países ha creado un problema debido a la imparable generación de residuos. Más aún, la recogida de residuos se realiza siguiendo una ruta predefinida que no tiene en cuenta el nivel real de los contenedores recogidos. Por lo tanto, optimizar la forma en que se recolectan los residuos presenta una oportunidad interesante. En este estudio, abordamos el problema de predecir la tasa de generación de residuos en condiciones reales, es decir, bajo incertidumbre. En particular, utilizamos una técnica neuroevolutiva profunda para diseñar automáticamente una red recurrente que encapsula el nivel de llenado de todos los contenedores de residuos en una ciudad a la vez, y estudiamos la idoneidad de nuestra propuesta cuando nos enfrentamos a datos ruidosos y defectuosos. Validamos nuestra propuesta utilizando un caso real, que consta de más de doscientos contenedores de residuos ubicados en una ciudad de España, y comparamos nuestros resultados con el estado del arte. Los resultados muestran que nuestra propuesta supera a todos sus competidores y que su precisión en un escenario del mundo real, es decir, bajo datos inciertos, es lo suficientemente buena para optimizar la planificación de la recolección de residuos.

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Biografía del autor/a

Andrés Camero, Universidad de Málaga

Departamento de Lenguajes y Ciencias de la Computación.

Jamal Toutouh, Instituto de Tecnología de Massachusetts

Laboratorio de Informática e Inteligencia Artificial del MIT.

Javier Ferrer, Universidad de Málaga

Departamento de Lenguajes y Ciencias de la Computación.

Enrique Alba, Universidad de Málaga

Departamento de Lenguajes y Ciencias de la Computación.

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Publicado

2019-08-23

Cómo citar

Camero, A., Toutouh, J., Ferrer, J., & Alba, E. (2019). Predicción de la producción de residuos con incertidumbre en la ciudad inteligente mediante neuroevolución profunda. Revista Facultad De Ingeniería Universidad De Antioquia, (93), 128–138. https://doi.org/10.17533/udea.redin.20190736

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