A deep learning architecture for energy service demand estimation in transport sector for Shared Socioeconomic Pathways

Siddharth Joshi, Brian Ó Gallachóir, James Glynn

Open source

DOI: 10.1038/s41598-023-30555-6
Published: 2023-03-02
Container: Scientific Reports
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-023-30555-6,
  title = {A deep learning architecture for energy service demand estimation in transport sector for Shared Socioeconomic Pathways},
  author = {Siddharth Joshi and Brian Ó Gallachóir and James Glynn},
  year = {2023},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-023-30555-6},
  url = {https://doi.org/10.1038/s41598-023-30555-6}
}

RIS

TY  - JOUR
TI  - A deep learning architecture for energy service demand estimation in transport sector for Shared Socioeconomic Pathways
AU  - Siddharth Joshi
AU  - Brian Ó Gallachóir
AU  - James Glynn
PY  - 2023
JO  - Scientific Reports
DO  - 10.1038/s41598-023-30555-6
UR  - https://doi.org/10.1038/s41598-023-30555-6
ER  -

APA

Joshi, S., Gallachóir, B. Ó., & Glynn, J. (2023). A deep learning architecture for energy service demand estimation in transport sector for Shared Socioeconomic Pathways. Scientific Reports. https://doi.org/10.1038/s41598-023-30555-6

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crossref · retrieved 2026-09-26T10:18:07.347Z