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Explainable Stacking-Based Learning Model for Traffic Forecasting
| 题名： | Explainable Stacking-Based Learning Model for Traffic Forecasting |
| 正文语种： | eng |
| 作者： | Chengyong Chen;Jinghan Liu;Yuexiang Li;Yan Zhang |
| 作者单位： | Shandong High-Speed Infrastructure Construction Co. Ltd. Shandong Expressway Mansion No. 8 Longao North Rd. Lixia District Jinan Shandong 250098 China;School of Engineering and Applied Sciences Univ. of Pennsylvania Philadelphia PA;Shandong High |
| 关键词： | Traffic flow forecasting; Stacked machine learning ensembles; Interpretability of spatial-temporal features; Resampling-based consensus clustering |
| 摘要： | This paper implements a two-staged ensemble learning model for traffic forecasting, focusing on the interpretability of predictions. The stacking model leverages the advantages of its diverse component learning models. Experiments on high-dimensional and |
| 出版年： | 2024 |
| 期刊名称： | Journal of Transportation Engineering, Part A. Systems |
| 卷： | 150 |
| 期： | 4 |
| 页码： | 04024006.1-04024006.12 |
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