@misc{10481/107457,
year = {2025},
month = {12},
url = {https://hdl.handle.net/10481/107457},
abstract = {Regression analysis is a versatile tool with numerous applications across diverse domains. Its utility extends to several tasks, including forecasting, inverse modeling, anomaly detection, and pattern identification. Over the years, researchers have mainly focused on two regression categories: parametric and non-parametric analysis. In light of the benefits and drawbacks of both methods, this work introduces a semi-parametric approach, combining regression accuracy and interpretability. This is achieved by designing a hybrid model, that includes a physics-based sub-model and a neural network. The proposed data-driven pipeline is applied to a relevant case study from the energy sector, namely the analysis of building energy consumption, achieving high accuracy compared to the parametric approach. Results demonstrate an increase in the mean coefficient of determination, from 0.77 to 0.94, with a MAPE drop from 5.5 % to 2.2 %. Meanwhile, the semi-parametric model allows the assessment of the thermal behavior of the buildings, thereby offering an improvement over black-box approaches.},
organization = {European Union NextGenerationEU/PRTR - Spanish Ministry of Economic Affairs and Digital Transformation (IA4TES project, MIA.2021.M04.0008)},
organization = {FEDER/Junta de Andalucía – (D3S project, P21.00247; SE2021 UGR IFMIF-DONES)},
organization = {MICIU/AEI/10.13039/501100011033 (SINERGY project, PID2021.125537NA.I00)},
publisher = {Elsevier},
keywords = {Semi-parametric models},
keywords = {Regression analysis},
keywords = {Hybrid models},
title = {Experimental application of a semi-parametric model for interpretable and accurate egression analysis of building energy consumption},
doi = {10.1016/j.enbuild.2025.116495},
author = {Eiraudo, Simone and Gijón, Alfonso and Manjavacas, Antonio and Schiera, Daniele Salvatore and Barbierato, Luca and Molina Solana, Miguel José and Gómez Romero, Juan and Giannantonio, Roberta and Bottaccioli, Lorenzo and Lanzini, Andrea},
}