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Adaptive surrogate modeling for high-dimensional spatio-temporal output
This paper develops an adaptive surrogate modeling method for problems with very high-dimensional spatio-temporal outputs. The analysis of...
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MDSTF: a multi-dimensional spatio-temporal feature fusion trajectory prediction model for autonomous driving
In the field of autonomous driving, trajectory prediction of traffic agents is an important and challenging problem. Fully capturing the complex...
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Channel spatio-temporal convolutional network for pedestrian trajectory prediction
Pedestrian trajectory prediction is a crucial technology for agents to assist human beings, which remains highly challenging due to the complex...
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Pedestrian trajectory prediction based on spatio-temporal attention mechanism
Mining and modeling city residents’ long-term and short-term preferences from their historical trajectory data is a key issue in trajectory...
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MSSTN: a multi-scale spatio-temporal network for traffic flow prediction
Spatio-temporal feature extraction and fusion are crucial to traffic prediction accuracy. However, the complicated spatio-temporal correlations and...
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Spatio-temporal analysis of georeferenced time-series applied to structural monitoring
Spatio-temporal (S-T) analysis is not typical in structural monitoring applications of buildings and infrastructure. However, monitoring always...
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Traffic Flow Forecasting of Graph Convolutional Network Based on Spatio-Temporal Attention Mechanism
Accurate traffic flow forecasting is a prerequisite guarantee for the realization of intelligent transportation. Due to the complex time and space...
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Multi-Encoder Spatio-Temporal Feature Fusion Network for Electric Vehicle Charging Load Prediction
Electric vehicles (EVs) have been initiated as a preference for decarbonizing road transport. Accurate charging load prediction is essential for the...
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TrajectoFormer: Transformer-Based Trajectory Prediction of Autonomous Vehicles with Spatio-temporal Neighborhood Considerations
Accurate trajectory prediction of autonomous vehicles is crucial for ensuring road safety. Predicting precise and accurate trajectories is still...
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Deep learning method for super-resolution reconstruction of the spatio-temporal flow field
The high-resolution (HR) spatio-temporal flow field plays a decisive role in describing the details of the flow field. In the acquisition of the HR...
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Spatio-temporal dynamics of an SIS model with nonlinear incidence and nonlocal disease transmission
Investigation of the spatio-temporal patterns exhibited by infected communities sharing the same spatial region is the focus of many researchers....
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Spatio-temporal graph cross-correlation auto-encoding network for wind power prediction
The rate of wind energy shows a sharp increase in recent years. Due to the instability, it is necessary to accurately predict the value of wind power...
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Agent-Based Modeling of the Spatio-temporal Distribution of Sahelian Transhumant Herds
Sahelian transhumance is a seasonal pastoral mobility between the transhumant’s terroir of origin and one or more host terroirs. Sahelian...
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Smart Diabetic Prediction: An Intelligent IoT-Based Diabetic Monitoring System with Stacked Spatio Temporal Features-Based Multiscale Dilated Deep Temporal Convolutional Network
Most of people are affected with the disease of diabetes worldwide and the affection rate has increased around the world over the years. Researchers...
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Time Series Processing Scheme Based on Deep Learning and Spatio-temporal Network Modeling
In order to study how massive data with periodic and tidal performance influences identification and processing in present network, this paper...
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SpaTiaL: monitoring and planning of robotic tasks using spatio-temporal logic specifications
Many tasks require robots to manipulate objects while satisfying a complex interplay of spatial and temporal constraints. For instance, a table...
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A Scalable Spatio-Temporal Analytics Framework for Urban Networks
Numerous real-world processes and events, especially in the urban domain, are represented with spatio-temporal transactional data (STTD): examples...
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CTDM: cryptocurrency abnormal transaction detection method with spatio-temporal and global representation
With the rapid advances in computing and networking technologies, there have led to the creation of a novel and booming set of payment services,...
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A Neural Network-based Suture-tension Estimation Method Using Spatio-temporal Features of Visual Information and Robot-state Information for Robot-assisted Surgery
In robot-assisted minimally invasive surgery, there is a risk of skin tissue damage or suture failure at the suture site owing to incomplete tension....
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Multi-view Bayesian spatio-temporal graph neural networks for reliable traffic flow prediction
Accurate traffic flow prediction is critically essential to transportation safety and Intelligent Transportation Systems (ITS). Existing approaches...
