Mobility trajectory generation: a survey
Mobility trajectory data is of great significance for mobility pattern study, urban computing,
and city science. Self-driving, traffic prediction, environment estimation, and many other …
and city science. Self-driving, traffic prediction, environment estimation, and many other …
Contrastive Learning-Based Adaptive Graph Fusion Convolution Network With Residual-Enhanced Decomposition Strategy for Traffic Flow Forecasting
C Ji, Y Xu, Y Lu, X Huang, Y Zhu - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Traffic flow prediction is the foundation of traffic scheduling and a major component of
intelligent transportation systems (ITSs). Accurate traffic flow prediction is crucial for …
intelligent transportation systems (ITSs). Accurate traffic flow prediction is crucial for …
Latent Factor Analysis Model With Temporal Regularized Constraint for Road Traffic Data Imputation
H Yang, M Lin, H Chen, X Luo… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITSs) are designed to alleviate traffic congestion and
provide convenience for travelers or decision-makers. However, the challenge lies in …
provide convenience for travelers or decision-makers. However, the challenge lies in …
A gentle introduction and tutorial on deep generative models in transportation research
Deep Generative Models (DGMs) have rapidly advanced in recent years, becoming
essential tools in various fields due to their ability to learn complex data distributions and …
essential tools in various fields due to their ability to learn complex data distributions and …
FedImpute: Personalized federated learning for data imputation with clusterer and auxiliary classifier
Y Li, S Guo, X Guo, P Zhao, X Ren, H Wang - Expert Systems with …, 2025 - Elsevier
Missing data is a prevalent challenge in real-world applications, hindering the usability and
quality of datasets. Data imputation, a method to substitute missing values, offers a solution …
quality of datasets. Data imputation, a method to substitute missing values, offers a solution …
A New Data Completion Perspective on Sparse CrowdSensing: Spatiotemporal Evolutionary Inference Approach
Mobile CrowdSensing (MCS) has emerged as a popular paradigm to engage mobile users
in collaborative sensing tasks. However, its performance is hindered by its limited …
in collaborative sensing tasks. However, its performance is hindered by its limited …
[PDF][PDF] Spatio-Temporal Bi-LSTM Based Variational Auto-Encoder for Multivariate IoT Data Imputation.
VV Guggilam, G Sundaram - … Journal of Intelligent Engineering & Systems, 2024 - inass.org
In the relam of the Internet of Things (IoT), prevalence of missing data due to continuous
data collection by smart devices necessitates the essential preliminary step of data …
data collection by smart devices necessitates the essential preliminary step of data …