Integrating Spatial Self-Attention and Convolution Networks for Improved Car-Sharing Demand Forecasting

Integrating Spatial Self-Attention and Convolution Networks for Improved Car-Sharing Demand Forecasting

The core challenge facing the field of car-sharing demand forecasting lies in the innovative construction of models that effectively capture the intricate spatio-temporal variations in the data. Current methods face two particularly significant challenges: first, Current models struggle to capture t...

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Bibliographic Details
Main Authors: Shengjun Qin, Jiaying Qin, Zhi Liu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Convolution networks
car-sharing
demand forecasting
spatio-temporal feature
Online Access:https://ieeexplore.ieee.org/document/10798450/

Internet

https://ieeexplore.ieee.org/document/10798450/

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