Missing traffic data imputation for artificial intelligence in intelligent transportation systems: review of methods, limitations, and challenges
RKC Chan, JMY Lim, R Parthiban - IEEE Access, 2023 - ieeexplore.ieee.org
Missing data in Intelligent Transportation Systems (ITS) could lead to possible errors in the
analyses of traffic data. Applying Artificial Intelligence (AI) in these circumstances can …
analyses of traffic data. Applying Artificial Intelligence (AI) in these circumstances can …
An Effective Imputation Method Using Data Enrichment for Missing Data of Loop Detectors in Intelligent Traffic Control Systems
In intelligent traffic control systems, the features extracted by loop detectors are insufficient to
accurately impute missing data. Most of the existing imputation methods use only these …
accurately impute missing data. Most of the existing imputation methods use only these …
A customized data fusion tensor approach for interval-wise missing network volume imputation
Traffic missing data imputation is a fundamental demand and crucial application for real-
world intelligent transportation systems. The wide imputation methods in different missing …
world intelligent transportation systems. The wide imputation methods in different missing …
A Data Fusion CANDECOMP-PARAFAC Method for Interval-wise missing network volume imputation
Traffic missing data imputation is a fundamental demand and crucial application for real-
world intelligent transportation systems. The wide imputation methods in different missing …
world intelligent transportation systems. The wide imputation methods in different missing …
Machine Learning Based missing data Imputation in Categorical Datasets
In order to predict and fill in the gaps in categorical datasets, this research looked into the
use of machine learning algorithms. The emphasis was on ensemble models constructed …
use of machine learning algorithms. The emphasis was on ensemble models constructed …
Attention‐Based Gated Recurrent Graph Convolutional Network for Short‐Term Traffic Flow Forecasting
P Lou, Z Wu, J Hu, Q Liu, Q Wei - Journal of Mathematics, 2023 - Wiley Online Library
Traffic flow prediction is the basis of dynamic strategies and applications of intelligent
transportation systems (ITS). Accurate traffic flow prediction is of great practical significance …
transportation systems (ITS). Accurate traffic flow prediction is of great practical significance …
[HTML][HTML] A Classification Method for Incomplete Mixed Data Using Imputation and Feature Selection
G Li, Q Zheng, Y Liu, X Li, W Qin, X Diao - Applied Sciences, 2024 - mdpi.com
Data missing is a ubiquitous problem in real-world systems that adversely affects the
performance of machine learning algorithms. Although many useful imputation methods are …
performance of machine learning algorithms. Although many useful imputation methods are …
Spatial Network-Wide Traffic Flow Imputation With Graph Neural Network
Traffic data plays an essential role in Intelligent Transportation Systems (ITS) and offers
numerous advantages, including efficient traffic control and system performance …
numerous advantages, including efficient traffic control and system performance …
[PDF][PDF] Spatiotemporal Graph Convolutional Neural Network for Robust and Accurate Traffic Flow Prediction
Y Liu - 2024 - research.tue.nl
Spatiotemporal Graph Convolutional Neural Network for Robust and Accurate Traffic Flow
Prediction Page 1 Spatiotemporal Graph Convolutional Neural Network for Robust and Accurate …
Prediction Page 1 Spatiotemporal Graph Convolutional Neural Network for Robust and Accurate …