ArticleScientific reports2026
Enhanced short-term traffic flow forecasting using a meteorological spatio-temporal transformer with multi-head attention and whale optimization.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
Rapid urbanization and increasing vehicle ownership have intensified traffic congestion, creating serious social, economic, and environmental challenges. Accurate short-term traffic flow prediction is therefore essential for effective urban traffic management and congestion mitigation. While traditional models struggle with the non-linear, dynamic nature of traffic data, our approach proposes an optimized synthesis named the Meteorological Spatio-Temporal Transformer Network with Multi-Head Attention and Whale Optimization Algorithm (MSTT-MHA-WOA). This framework enhances prediction by uniquely integrating non-linear meteorological features and, critically, by using the Whale Optimization Algorithm (WOA) for autonomous hyper parameter tuning. We evaluate the model's robust and consistent performance across six diverse, real-world traffic scenarios-a crucial test of its generalization capability under complex conditions.
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