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journal article·2025-04-01Open access

Enhanced hourly temperature prediction using advanced ensemble neural networks for energy system efficiency optimization in hyper-arid regions

Abdennasser Dahmani, Ikram Kouidri, Nadjem Bailek, Lotfi Mouni, Shabana Urooj, Jihad A. Younis, Bilel Zerouali, El-Sayed M El-Kenawy, Celso Augusto Guimarães Santos, Abdel-Nasser Sharkawy

AIP Advances· Volume 15· Issue 4
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Abstract

This paper presents advanced techniques for air temperature forecasting based on the relationship between meteorological variables and feedforward neural network models aimed at improving prediction accuracy. An optimal single neural network model was developed, and optimization through dataset partitioning resulted in high predictive preformance, with all correlation coefficients exceeding 0.97 in the test phase and a root mean square error (RMSE) of 1.5587. Additionally, a bootstrap-aggregated neural network (BANN) model comprising 30 networks in a stacked ensemble was implemented, yielding robust results; both validation and testing correlation coefficients were close to the ideal value. Sensitivity analysis further revealed that true solar time, extraterrestrial radiation, and wind speed were the most influential predictors—an outcome that is consistent with their physical relevance to temperature variation. Moreover, the model’s validity was confirmed through applicability domain analysis using the Williams plot, which showed that over 97% of the predictions fell within acceptable error limits. A comparative evaluation against other existing models demonstrated the superior predictive performance of the proposed approach, reinforcing the potential of the BANN model for accurate air temperature forecasting under diverse meteorological conditions.
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Research context

Composites

OpenAlex topics: Energy Load and Power Forecasting · Solar Radiation and Photovoltaics · Hydrological Forecasting Using AI

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical Engineering, Faculty of Applied Sciences, University of Bouira 1 , Bouira 10000,

Laboratory of Biomaterials and Transport Phenomena (LBMPT), University of Medea 2 , Urban Pole, 26000 Medea,

Department of Mechanical Engineering, Faculty of Science and Technology, GIDD Industrial Engineering and Sustainable Development Laboratory, University of Relizane 3 , Bourmadia, 48000 Relizane,

Laboratory of Mathematics Modeling and Applications, Department of Mathematics and Computer Science, Faculty of Sciences and Technology, Ahmed Draia University of Adrar 4 , Adrar,

5 Jadara Research Center, Jadara University, Irbid 21110, Jordan

Laboratoire de Gestion et Valorisation des Ressources Naturelles et Assurance Qualité, Faculté SNVST, Université de Bouira 6 , 10000 Bouira,

Department of Electrical Engineering, College of Engineering, Princess Nourah Bint Abdulrahman University 7 , P.O. Box 84428, Riyadh 11671,

Department of Mathematics, Aden University 8 , Aden,

Laboratory of Architecture, Cities and Environment, Faculty of Civil Engineering and Architecture, Department of Hydraulic, Hassiba Benbouali, University of Chlef 9 , B.P. 78C, Ouled Fares, Chlef 02180,

Vegetal Chemistry-Water-Energy Laboratory, Faculty of Civil Engineering and Architecture, Depart-ment of Hydraulic, Hassiba Benbouali, University of Chlef 10 , B.P. 78C, Ouled Fares, Chlef 02180,

School of ICT, Faculty of Engineering, Design and Information & Communications Technology (EDICT), Bahrain Polytechnic 11 , P.O. Box 33349, Isa Town,

Applied Science Research Center, Applied Science Private University 12 , Amman,

Department of Civil and Environmental Engineering, Federal University of Paraíba 13 , João Pessoa 58051-900,

Mechanical Engineering Department, Faculty of Engineering, South Valley University 14 , Qena 83523,

Funding

Princess Nourah Bint Abdulrahman University

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