Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))

S. Mateo-Barcos; D. Ribó-Pérez; J. Rodríguez-García; M. Alcázar-Ortega

doi:10.1016/j.egyr.2024.04.017

Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))

S. Mateo-Barcos, D. Ribó-Pérez^*, J. Rodríguez-García, M. Alcázar-Ortega

^*Corresponding author for this work

Energy and Industry

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Abstract

The authors regret <To not have included during the publication process the acknowledgement to a project that has been part of this work and want to include in the acknowledgements part: This work was partially supported by the Grant TED2021-129722B-C31 (ALIVE-DER), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. >. The authors would like to apologise for any inconvenience caused.

Original language	English
Pages (from-to)	4452
Number of pages	1
Journal	Energy Reports
Volume	11
DOIs	https://doi.org/10.1016/j.egyr.2024.04.017
Publication status	Published - 2024

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Mateo-Barcos, S., Ribó-Pérez, D., Rodríguez-García, J., & Alcázar-Ortega, M. (2024). Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023)). Energy Reports, 11, 4452. https://doi.org/10.1016/j.egyr.2024.04.017

Mateo-Barcos, S. ; Ribó-Pérez, D. ; Rodríguez-García, J. et al. / Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023)). In: Energy Reports. 2024 ; Vol. 11. pp. 4452.

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title = "Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))",

abstract = "The authors regret <To not have included during the publication process the acknowledgement to a project that has been part of this work and want to include in the acknowledgements part: This work was partially supported by the Grant TED2021-129722B-C31 (ALIVE-DER), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. >. The authors would like to apologise for any inconvenience caused.",

author = "S. Mateo-Barcos and D. Rib{\'o}-P{\'e}rez and J. Rodr{\'i}guez-Garc{\'i}a and M. Alc{\'a}zar-Ortega",

year = "2024",

doi = "10.1016/j.egyr.2024.04.017",

language = "English",

volume = "11",

pages = "4452",

journal = "Energy Reports",

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Mateo-Barcos, S, Ribó-Pérez, D, Rodríguez-García, J & Alcázar-Ortega, M 2024, 'Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))', Energy Reports, vol. 11, pp. 4452. https://doi.org/10.1016/j.egyr.2024.04.017

Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023)). / Mateo-Barcos, S.; Ribó-Pérez, D.; Rodríguez-García, J. et al.
In: Energy Reports, Vol. 11, 2024, p. 4452.

Research output: Contribution to journal › Comment/Letter to the editor › Scientific › peer-review

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T1 - Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))

AU - Mateo-Barcos, S.

AU - Ribó-Pérez, D.

AU - Rodríguez-García, J.

AU - Alcázar-Ortega, M.

PY - 2024

Y1 - 2024

N2 - The authors regret <To not have included during the publication process the acknowledgement to a project that has been part of this work and want to include in the acknowledgements part: This work was partially supported by the Grant TED2021-129722B-C31 (ALIVE-DER), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. >. The authors would like to apologise for any inconvenience caused.

AB - The authors regret <To not have included during the publication process the acknowledgement to a project that has been part of this work and want to include in the acknowledgements part: This work was partially supported by the Grant TED2021-129722B-C31 (ALIVE-DER), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. >. The authors would like to apologise for any inconvenience caused.

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Mateo-Barcos S, Ribó-Pérez D, Rodríguez-García J, Alcázar-Ortega M. Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023)). Energy Reports. 2024;11:4452. doi: 10.1016/j.egyr.2024.04.017

Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))

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