Quantum neural networks with data re-uploading for urban traffic time series forecasting

Abstract Accurate traffic forecasting plays a crucial role in modern Intelligent Transportation Systems (ITS), as it enables real-time traffic flow management, reduces congestion, and improves the overall efficiency of urban transportation networks. With the rise of Quantum Machine Learning (QML), i...

Popoln opis

Bibliografske podrobnosti

Principais autores:	Nikolaos Schetakis, Paolo Bonfini, Negin Alisoltani, Konstantinos Blazakis, Symeon I. Tsintzos, Alexis Askitopoulos, Davit Aghamalyan, Panagiotis Fafoutellis, Eleni I. Vlahogianni
Format:	Artigo
Jezik:	Inglês
Izdano:	Nature Portfolio 2025-06-01
Serija:	Scientific Reports
Online dostop:	https://doi.org/10.1038/s41598-025-04546-8
Oznake:	Označite Brez oznak, prvi označite!