التفاصيل البيبلوغرافية
| العنوان: |
Traffic Flow Prediction with Attention Mechanism Based on TS-NAS |
| المؤلفون: |
Cai Zhao, Ruijing Liu, Bei Su, Lei Zhao, Zhiyong Han, Wen Zheng |
| المصدر: |
Sustainability; Volume 14; Issue 19; Pages: 12232 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2022 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
prediction of traffic flow, temporal attention mechanism, TS-NAS, spatial attention mechanism |
| جغرافية الموضوع: |
agris |
| الوصف: |
The prediction of traffic flow is of great significance in the traffic field. However, because of the high uncertainty and complexity of traffic data, it is challenging that doing traffic flow prediction. Most of the existing methods have achieved good results in traffic flow prediction, but are not accurate enough to capture the dynamic temporal and spatial relationship of data by using the structural information of traffic flow. In this study, we propose a traffic flow prediction method with temporal attention mechanism and spatial attention mechanism based on neural architecture search (TS-NAS). Firstly, based on temporal and spatial attention mechanisms, we design a new attention mechanism. Secondly, we define a novel model to learn temporal flow and space flow in traffic network. Finally, the proposed method uses different modules about time, space and convolution and neural architecture search to be used for optimizing the model. We use two datasets to test the method. Experimental results show that the performance of the method is better than that of the existing method. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
Sustainable Urban and Rural Development; https://dx.doi.org/10.3390/su141912232 |
| DOI: |
10.3390/su141912232 |
| الاتاحة: |
https://doi.org/10.3390/su141912232 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.A45DBAA |
| قاعدة البيانات: |
BASE |