Neural Network for Sky Darkness Level Prediction in Rural Areas

A neural network was developed using the Multilayer Perceptron (MLP) model to predict the darkness value of the night sky in rural areas. For data collection, a photometer was placed in three different rural locations in the province of Cáceres, Spain, recording darkness values over a period of 23 m...

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Veröffentlicht in:Sustainability 2024-09, Vol.16 (17), p.7795
Hauptverfasser: Martínez-Martín, Alejandro, Jaramillo-Morán, Miguel Ángel, Carmona-Fernández, Diego, Calderón-Godoy, Manuel, González, Juan Félix González
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Sprache:eng
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Zusammenfassung:A neural network was developed using the Multilayer Perceptron (MLP) model to predict the darkness value of the night sky in rural areas. For data collection, a photometer was placed in three different rural locations in the province of Cáceres, Spain, recording darkness values over a period of 23 months. The recorded data were processed, debugged, and used as a training set (75%) and validation set (25%) in the development of an MLP capable of predicting the darkness level for a given date. The network had a single hidden layer of 10 neurons and hyperbolic activation function, obtaining a coefficient of determination (R2) of 0.85 and a mean absolute percentage error (MAPE) of 6.8%. The developed model could be employed in unpopulated rural areas for the promotion of sustainable astronomical tourism.
ISSN:2071-1050
2071-1050
DOI:10.3390/su16177795