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北京航空航天大学 [6]
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兰州理工大学 [1]
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期刊论文 [9]
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A deep learning traffic flow prediction framework based on multi-channel graph convolution
期刊论文
TRANSPORTATION PLANNING AND TECHNOLOGY, 2021, 卷号: 44, 期号: 8, 页码: 887-900
作者:
Zhao, Yuanmeng
;
Cao, Jie
;
Zhang, Hong
;
Liu, Zongli
收藏
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浏览/下载:7/0
  |  
提交时间:2021/12/17
Traffic flow
deep learning
graph convolution (GCN)
Long Short-Term Memory (LSTM)
spatial-temporal features
A Spatial-Temporal Positioning Algorithm Using Residual Network and LSTM
期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 卷号: 69, 期号: 11, 页码: 9251-9261
作者:
Wang, Rongrong
;
Luo, Haiyong
;
Wang, Qu
;
Li, Zhaohui
;
Zhao, Fang
收藏
  |  
浏览/下载:43/0
  |  
提交时间:2020/12/10
Wireless fidelity
Feature extraction
Fingerprint recognition
Residual neural networks
Deep learning
Robustness
Degradation
Convolutional neural network (CNN)
indoor positioning
long short-term memory (LSTM)
residual network
spatial-temporal
A spatial-temporal attention model for human trajectory prediction
期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2020, 卷号: 7, 期号: 4, 页码: 965-974
作者:
Zhao, Xiaodong
;
Chen, Yaran
;
Guo, Jin
;
Zhao, Dongbin
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2020/08/03
Attention mechanism
long-short term memory (LSTM)
spatial-temporal model
trajectory prediction
A Spatial-Temporal Attention Model forHuman Trajectory Prediction
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2020, 卷号: 7, 期号: 4, 页码: 965-974
作者:
Xiaodong Zhao
;
Yaran Chen
;
Jin Guo
;
Dongbin Zhao
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2021/03/11
Attention mechanism
long-short term memory (LSTM)
spatial-temporal model
trajectory prediction
A novel residual graph convolution deep learning model for short-term network-based traffic forecasting
期刊论文
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2019, 卷号: 34, 期号: 5, 页码: 27
作者:
Zhang, Yang
;
Cheng, Tao
;
Ren, Yibin
;
Xie, Kun
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2020/03/20
Short-term traffic forecasting
spatial-temporal dependency
network topology
graph convolution
residual long short-term memory
Deep-learning-based Wind Speed Forecasting Considering Spatial-temporal Correlations with Adjacent Wind Turbines
期刊论文
2019, 页码: 623-632
作者:
Shi, Xiaoyu
;
Huang, Shengzhi
;
Huang, Qiang
;
Lei, Xuewen
;
Li, Jiangfeng
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2019/12/20
Wind speed prediction
spatial-temporal correlation
wavelet coherence transformation analysis
long short term memory
Improved Panoramic Representation via Bidirectional Recurrent View Aggregation for Three-Dimensional Model Retrieval
期刊论文
IEEE COMPUTER GRAPHICS AND APPLICATIONS, 2019, 卷号: 39, 页码: 65-76
作者:
Xu, Cheng
;
Zhang, Cheng
;
Zhou, Xiaochen
;
Leng, Biao
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2019/12/30
Deep neural networks
3 d model retrievals
3D shape retrieval
Effective approaches
High-level features
Panoramic informations
Panoramic representation
Shape information
Spatial correlations
Long short-term memory
Traffic congestion prediction based on long-short term memory neural network models
会议论文
CICTP 2017: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation - Proceedings of the 17th COTA International Conference of Transportation Professionals
作者:
Chen, M.
;
Yu, G.
;
Chen, P.
;
Wang, Y.
收藏
  |  
浏览/下载:11/0
  |  
提交时间:2019/12/30
Brain
Complex networks
Deep learning
Forecasting
Long short-term memory
Motor transportation
Speed
Urban transportation
Congestion prediction
Learning Theory
Mathematical equations
Simulation technique
Spatial correlations
Temporal and spatial correlation
Traffic speed
Transportation researchers
Traffic congestion
Attentive crowd flow machines
会议论文
MM 2018 - Proceedings of the 2018 ACM Multimedia Conference
作者:
Liu, L.
;
Zhang, R.
;
Peng, J.
;
Li, G.
;
Du, B.
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2019/12/30
Data storage equipment
Forecasting
Street traffic control
Dynamic representation
Mobility datum
Spatial temporal model
Spatial-temporal features
State-of-the-art methods
Traffic flow prediction
Unified neural networks
Urban traffic management
Long short-term memory
A hybrid deep learning approach for urban expressway travel time prediction considering spatial-temporal features
会议论文
IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
作者:
Zhang, Z.
;
Chen, P.
;
Wang, Y.
;
Yu, G.
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/30
Brain
Convolution
Forecasting
Highway traffic control
Intelligent systems
Intelligent vehicle highway systems
Long short-term memory
Traffic congestion
Travel time
Convolution neural network
Convolutional neural network
Learning neural networks
Non-parametric algorithm
Spatial-temporal features
Temporal correlations
Travel time forecasting
Travel time prediction
Deep learning
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