题名 | Traffic Data Imputation with Ensemble Convolutional Autoencoder |
作者 | |
通讯作者 | Yu,James J.Q. |
DOI | |
发表日期 | 2021-09-19
|
ISBN | 978-1-7281-9143-0
|
会议录名称 | |
卷号 | 2021-September
|
页码 | 1340-1345
|
会议日期 | 19-22 Sept. 2021
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会议地点 | Indianapolis, IN, USA
|
摘要 | Intelligent transportation systems and related applications rely on high-quality traffic data. However, the data collected in real-world is often incomplete, which compromises the system performance. Traffic data imputation estimates the missing values by analyzing traffic flow features, therefore can improve the performance of related applications. Traditional imputation methods mainly focus on isolated traffic data sensors or road sections and show their limitations in representing complex spatial-temporal features. In this paper, we propose a novel ensemble model named ensemble convolutional auto encoder for the task. The observed values, together with the missing points are reconstructed into a two-dimensional matrix by the extracted spatial-temporal relation. Convolutional and deconvolutional layers are adopted to encode and decode spatial-temporal features, respectively. Besides, we train autoencoders with different input feature maps and ensemble the outputs by linear combination. Experimental results show that compared with other traffic data imputation methods, the proposed method can achieve better accuracy and has stable performance under various missing data scenarios with different types and rates. |
关键词 | |
学校署名 | 第一
; 通讯
|
语种 | 英语
|
相关链接 | [Scopus记录] |
收录类别 | |
EI入藏号 | 20214511115126
|
EI主题词 | Intelligent systems
; Learning systems
|
EI分类号 | Information Theory and Signal Processing:716.1
; Artificial Intelligence:723.4
|
Scopus记录号 | 2-s2.0-85118452635
|
来源库 | Scopus
|
全文链接 | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9564839 |
引用统计 |
被引频次[WOS]:9
|
成果类型 | 会议论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/255440 |
专题 | 工学院_计算机科学与工程系 |
作者单位 | Southern University of Science and Technology,Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,Department of Computer Science and Engineering,Shenzhen,China |
第一作者单位 | 计算机科学与工程系 |
通讯作者单位 | 计算机科学与工程系 |
第一作者的第一单位 | 计算机科学与工程系 |
推荐引用方式 GB/T 7714 |
Ye,Yongchao,Zhang,Shuyu,Yu,James J.Q.. Traffic Data Imputation with Ensemble Convolutional Autoencoder[C],2021:1340-1345.
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条目包含的文件 | 条目无相关文件。 |
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