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Updated: Jun 28, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

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使用自我注意力和多图形网络进行适应的时空流量预测.

Basma Alsehaimi1,2, Ohoud Alzamzami1, Nahed Alowidi1

  • 1Department of Computer Science, King AbdulAziz University, Jeddah 21589, Saudi Arabia.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
概括

这项研究引入了基于时间空间注意力的自适应多模型 (ASTAM),以改进交通流量预测. ASTAM通过准确地捕捉复杂的时空交通模式来增强智能交通系统.

关键词:
注意力机制注意力机制图表注意力网络的注意力网络.图形卷积网络的图形卷积网络.时间卷积网络交通流量预测和流量预测.

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相关概念视频

End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting the...