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  • Li Z L, Yu J, Zhang G W, et al. Dynamic spatio-temporal graph network with adaptive propagation mechanism for multivariate time series forecasting[J]. Expert Systems with Applications, 2023, 216: 119374. Link
  • Wang Z, Ding D, Liang X. TYRE: A dynamic graph model for traffic prediction[J]. Expert Systems with Applications, 2022: 119311. Link Code
  • Ma D, Zhu J, Song X B, et al. Traffic flow and speed forecasting through a Bayesian deep multi-linear relationship network[J]. Expert Systems with Applications, 2022: 119161. Link
  • Zeng J, Tang J. Combining knowledge graph into metro passenger flow prediction: A split-attention relational graph convolutional network[J]. Expert Systems with Applications, 2023, 213: 118790. Link
  • Bao J, Kang J, Yang Z, et al. Forecasting network-wide multi-step metro ridership with an attention-weighted multi-view graph to sequence learning approach[J]. Expert Systems with Applications, 2022: 118475. Link
  • Zheng G, Chai W K, Katos V. A dynamic spatial–temporal deep learning framework for traffic speed prediction on large-scale road networks[J]. Expert Systems with Applications, 2022: 116585. Link
  • Reza S, Ferreira M C, Machado J J M, et al. A multi-head attention-based transformer model for traffic flow forecasting with a comparative analysis to recurrent neural networks[J]. Expert Systems with Applications, 2022: 117275. Link
  • Zhao J, Liu Z, Sun Q, et al. Attention-based Dynamic Spatial-Temporal Graph Convolutional Networks for Traffic Speed Forecasting[J]. Expert Systems with Applications, 2022: 117511. Link
  • Xue G, Liu S, Ren L, et al. Forecasting the subway passenger flow under event occurrences with multivariate disturbances[J]. Expert Systems with Applications, 2022, 188: 116057. Link
  • Terroso-Saenz F, Flores R, Muñoz A. Human mobility forecasting with region-based flows and geotagged Twitter data[J]. Expert Systems with Applications, 2022: 117477. Link Code
  • Ma J, Chan J, Rajasegarar S, et al. Multi-attention graph neural networks for city-wide bus travel time estimation using limited data[J]. Expert Systems with Applications, 2022: 117057. Link
  • Zhu K, Zhang S, Li J, et al. Spatiotemporal multi-graph convolutional networks with synthetic data for traffic volume forecasting[J]. Expert Systems with Applications, 2022, 187: 115992. Link
  • Li H, Xiong S. Time-varying weight coefficients determination based on fuzzy soft set in combined prediction model for travel time[J]. Expert Systems with Applications, 2022, 189: 115998. Link