Neural Network for Sky Darkness Level Prediction in Rural Areas

Alejandro Martínez-Martín, Miguel Ángel Jaramillo-Morán, Diego Carmona-Fernández, Manuel Calderón-Godoy and Juan Félix González González ()
Additional contact information
Alejandro Martínez-Martín: Department of Applied Physic, School of Industrial Engineering, University of Extremadura, Avda. de Elvas, S/N, 06006 Badajoz, Spain
Miguel Ángel Jaramillo-Morán: Department of Electrical Engineering, Electronics and Automation, School of Industrial Engineering, University of Extremadura, Avda. de Elvas, S/N, 06006 Badajoz, Spain
Diego Carmona-Fernández: Department of Electrical Engineering, Electronics and Automation, School of Industrial Engineering, University of Extremadura, Avda. de Elvas, S/N, 06006 Badajoz, Spain
Manuel Calderón-Godoy: Department of Electrical Engineering, Electronics and Automation, School of Industrial Engineering, University of Extremadura, Avda. de Elvas, S/N, 06006 Badajoz, Spain
Juan Félix González González: Department of Applied Physic, School of Industrial Engineering, University of Extremadura, Avda. de Elvas, S/N, 06006 Badajoz, Spain

Sustainability, 2024, vol. 16, issue 17, 1-13

Abstract: 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 (R 2 ) 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.

Keywords: neural network; MLP; night sky brightness; NSB; photometer; astro-tourism; artificial neuron; stargazing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/17/7795/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/17/7795/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:17:p:7795-:d:1473219

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().