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利用自适应灰色预测区间模型量化实时交通状况的不确定性

IF 3.6 2区 工程技术 Q2 TRANSPORTATION
Transportmetrica A-Transport Science Pub Date : 2024-08-26 DOI:10.1080/23249935.2024.2394522
Zhanguo Song, Xinran Wang, Wei Huang, Meiye Li, Xiaobin Zhong, Jianhua Guo
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引用次数: 0

摘要

不确定性量化对于做出可靠的交通决策非常重要。对于基于灰色的不确定性量化方法，大多数模型的数据分类方法都无法对不确定性进行量化。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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Real-time traffic condition uncertainty quantification using adaptive grey prediction interval model
Uncertainty quantification is important for making reliable transportation decisions. For grey-based uncertainty quantification approaches, the data classification methods for most models cannot yi...
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来源期刊
Transportmetrica A-Transport Science
Transportmetrica A-Transport Science TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
8.10
自引率
12.10%
发文量
55
期刊介绍： Transportmetrica A provides a forum for original discourse in transport science. The international journal''s focus is on the scientific approach to transport research methodology and empirical analysis of moving people and goods. Papers related to all aspects of transportation are welcome. A rigorous peer review that involves editor screening and anonymous refereeing for submitted articles facilitates quality output.
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