Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …
critical problem globally, resulting in negative consequences such as lost hours of additional …
A systematic review of generative adversarial imputation network in missing data imputation
Data missing has always occurred in data processing. To solve this problem, researchers
have improved the process methods of the missing data with diverse strategies, which range …
have improved the process methods of the missing data with diverse strategies, which range …
Continuous missing data imputation with incomplete dataset by generative adversarial networks–based unsupervised learning for long-term bridge health monitoring
H Jiang, C Wan, K Yang, Y Ding… - Structural Health …, 2022 - journals.sagepub.com
Wireless sensors are the key components of structural health monitoring systems. During the
signal transmission, sensor failure is inevitable, among which, data loss is the most common …
signal transmission, sensor failure is inevitable, among which, data loss is the most common …
Imputation of missing values in time series using an adaptive-learned median-filled deep autoencoder
Missing values are ubiquitous in industrial data sets because of multisampling rates, sensor
faults, and transmission failures. The incomplete data obstruct the effective use of data and …
faults, and transmission failures. The incomplete data obstruct the effective use of data and …
Bidirectional spatial–temporal traffic data imputation via graph attention recurrent neural network
Spatiotemporal traffic data is increasingly important in transportation services with the
development of intelligent transportation system (ITS). However, due to various …
development of intelligent transportation system (ITS). However, due to various …
Missing data imputation on IoT sensor networks: Implications for on-site sensor calibration
NU Okafor, DT Delaney - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
IoT sensors are becoming increasingly important supplement to traditional monitoring
systems, particularly for in-situ based monitoring. Data collected using IoT sensors are often …
systems, particularly for in-situ based monitoring. Data collected using IoT sensors are often …
Leveraging generative AI for urban digital twins: a scoping review on the autonomous generation of urban data, scenarios, designs, and 3D city models for smart city …
The digital transformation of modern cities by integrating advanced information,
communication, and computing technologies has marked the epoch of data-driven smart city …
communication, and computing technologies has marked the epoch of data-driven smart city …
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 …
A comprehensive survey on traffic missing data imputation
Intelligent Transportation Systems (ITS) are essential and play a key role in improving road
safety, reducing congestion, optimizing traffic flow and facilitating the development of smart …
safety, reducing congestion, optimizing traffic flow and facilitating the development of smart …
A Survey of Generative AI for Intelligent Transportation Systems
Intelligent transportation systems play a crucial role in modern traffic management and
optimization, greatly improving traffic efficiency and safety. With the rapid development of …
optimization, greatly improving traffic efficiency and safety. With the rapid development of …