Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach.

Khan S, Mazhar T, Shahzad T, Ali T, Ayaz M, Ghadi YY, Aggoune EM, Hamam H

Open source

DOI
10.1038/s41598-025-04301-z
Published
2025 Jun 3
Container
Scientific reports
Publisher
Not recorded
Open access
yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1038/s41598-025-04301-z,
  title = {Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach.},
  author = {Khan S and Mazhar T and Shahzad T and Ali T and Ayaz M and Ghadi YY and Aggoune EM and Hamam H},
  year = {2025},
  journal = {Scientific reports},
  doi = {10.1038/s41598-025-04301-z},
  url = {https://doi.org/10.1038/s41598-025-04301-z}
}

RIS

TY  - JOUR
TI  - Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach.
AU  - Khan S
AU  - Mazhar T
AU  - Shahzad T
AU  - Ali T
AU  - Ayaz M
AU  - Ghadi YY
AU  - Aggoune EM
AU  - Hamam H
PY  - 2025
JO  - Scientific reports
DO  - 10.1038/s41598-025-04301-z
UR  - https://doi.org/10.1038/s41598-025-04301-z
ER  - 

APA

S, K., T, M., T, S., T, A., M, A., YY, G., EM, A., & H, H. (2025). Optimizing load demand forecasting in educational buildings using quantum-inspired particle swarm optimization (QPSO) with recurrent neural networks (RNNs):a seasonal approach.. Scientific reports. https://doi.org/10.1038/s41598-025-04301-z

Source records