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Updated: Jul 25, 2025

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通过深度学习增强旅行时间预测,对大流量数据的时间顺序信息进行时间顺序和追溯时间顺序信息

Claire Y T Chen1, Edward W Sun2, Ming-Feng Chang3

  • 1Montpellier Business School, Montpellier, France.

Annals of operations research
|June 26, 2023
PubMed
概括

一种新的深度学习方法,双向同度门循环单元 (BDIGRU),提高了智能运输的行程时间预测准确度. 这种方法有效地优化了车辆路线,提高了物流的可持续性.

关键词:
人工智能和机器学习大数据就是大数据.预测分析是一种预测分析.智能运输是一种智能运输.旅行时间 旅行时间

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