SE-MAConvLSTM framework.

<div><p>Traffic flow prediction is an important part of transportation management and planning. For example, accurate demand prediction of taxis and online car-hailing can reduce the waste of resources caused by empty cars. The prediction of public bicycle flow can be more reasonable to...

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Bibliographic Details
Main Author:	Rong Zhu (172093) (author)
Other Authors:	Jie Tang (46802) (author), Xuansen He (20390177) (author), Xianlai Zhou (20390180) (author), Xiaohui Huang (458909) (author), Fengyun Wu (12692969) (author), Songli Chen (11556928) (author)
Published:	2024
Subjects:	Biological Sciences not elsewhere classified Information Systems not elsewhere classified two problems mentioned traffic flow data time interval affects third problem mentioned temporal correlation existing last time interval historical flow data deep learning framework deep learning algorithm achieve higher accuracy convolutional neural network convolutional lstm network public bicycle flow cnn ), squeeze traffic flow prediction accurate demand prediction excitation network public bicycles prediction results transportation management three difficulties stfem ), results show respectively compared resources caused online car important part empty cars attention modules attention module aggregation module
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SE-MAConvLSTM framework.

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