Urban Traffic Volume Prediction using LSTM and Bi-LSTM: Performance Evaluation on the Metro Interstate Dataset

Urban traffic forecasting underpins the mitigation of congestion, enhancement of road safety, and reduction of emissions in intelligent transportation systems. We benchmark Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM) models on the Metro Interstate Traffic Volume dataset under an i...

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Detalhes bibliográficos

Principais autores:	Andri Pranolo, Shoffan Saifullah, Agung Bella Utama Putra, Rafał Dreżewski, Aji Prasetya Wibawa
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Fakultas Ilmu Komputer UMI 2025-10-01
coleção:	Ilkom Jurnal Ilmiah
Assuntos:	lstm bi-lstm deep learning time series forecasting urban traffic
Acesso em linha:	https://jurnal.fikom.umi.ac.id/index.php/ILKOM/article/view/3001
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