Highly Efficient Spatial–Temporal Correlation Basis for 5G IoT Networks [PDF]
Sensors, 2021 One of the major concerns in 5G IoT networks is that most of the sensor nodes are powered through limited lifetime, which seriously affects the performance of the networks.
Xiangping Gu, Mingxue Zhu, Liyun Zhuang
doaj +2 more sources
A Novel Approach to Calculate the Spatial–Temporal Correlation for Traffic Flow Based on the Structure of Urban Road Networks and Traffic Dynamic Theory [PDF]
Sensors, 2021 Determining the spatial–temporal correlation (STC) between roads can help clarify the operation characteristics of road traffic. Moreover, this correlation affects the utilization quality of traffic data in related research fields.
Mao Du, Lin Yang, Jiayu Tu
doaj +2 more sources
A Novel Reconstruction Method of K-Distributed Sea Clutter with Spatial–Temporal Correlation [PDF]
Sensors, 2020 The reconstruction of sea clutter plays an important role in target detection and recognition in a maritime environment. Reproducing the temporal and spatial correlations of real data simultaneously is always a problem in the reconstruction of sea ...
Mingyue Ding +4 more
doaj +2 more sources
User Incentive Mechanism Based on Spatial-Temporal Correlation for Crowd Sensing [PDF]
Jisuanji gongcheng, 2021 To realize effective user incentive in crowd sensing systems,this paper proposes two user incentive algorithms based on dominant and recessive spatial-temporal characteristics.The user incentive problem of dominant spatial-temporal correlation is ...
ZHOU Qiang, LI Peng, NIE Lei
doaj +1 more source
A Hybrid Model Integrating Local and Global Spatial Correlation for Traffic Prediction
IEEE Access, 2022 Accurate traffic prediction can effectively alleviate traffic congestion problems. The complex spatial correlation of traffic flow contributes to the challenging prediction problem.
Siyun Feng +4 more
doaj +1 more source
Sensors, 2022 Measurement error is non-negligible and crucial in SHM data analysis. In many applications of SHM, measurement errors are statistically correlated in space and/or in time for data from sensor networks.
He-Qing Mu +3 more
doaj +1 more source
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction
Sensors, 2023 The spatial–temporal prediction of traffic flow is very important for traffic management and planning. The most difficult challenges of traffic flow prediction are the temporal feature extraction and the spatial correlation extraction of nodes.
Xiaohui Huang +4 more
doaj +1 more source
Second-Order Spatial-Temporal Correlation Filters for Visual Tracking
Mathematics, 2022 Discriminative correlation filters (DCFs) have been widely used in visual object tracking, but often suffer from two problems: the boundary effect and temporal filtering degradation.
Yufeng Yu +5 more
doaj +1 more source
Spatial‐temporal correlation graph convolutional networks for traffic forecasting
IET Intelligent Transport Systems, 2023 Traffic forecasting, as a fundamental and challenging problem of intelligent transportation systems (ITS), has always been the focus of researchers. Nevertheless, accurate traffic forecasting still exists some problems due to the complex spatial‐temporal
Ru Huang +4 more
doaj +1 more source
Generating spatial precipitation ensembles: impact of temporal correlation structure [PDF]
Hydrology and Earth System Sciences, 2012 Sound spatially distributed rainfall fields including a proper spatial and temporal error structure are of key interest for hydrologists to force hydrological models and to identify uncertainties in the simulated and forecasted catchment response.
O. Rakovec +4 more
doaj +1 more source