Performance and improvement of deep learning algorithms based on LSTM in traffic flow prediction

Abstract Existing traffic flow prediction research lacks adaptability to complex traffic scenarios and has limited prediction accuracy. This paper introduces an improved LSTM (Long Short-Term Memory) algorithm and sliding window technology to improve the accuracy and stability of traffic flow predic...

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Autori principali:	Wei Xu, Eric Blancaflor, Mideth Abisado
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2025-03-01
Serie:	Discover Applied Sciences
Soggetti:	Traffic flow prediction City road Long short-term memory Bidirectional gated recurrent unit Hybrid model LSTM-BiGRU-attention model
Accesso online:	https://doi.org/10.1007/s42452-025-06702-1
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