Similar Papers

Paper Title
Journal
Date
Author
Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images
Tongge Huang ... Anuj Sharma
International Journal of Transportation Science and Technology | VOL. 12
Tongge Huang, et. al.Tongge Huang ... Anuj Sharma
01 Mar 2023
Learning Traffic as Videos: A Spatio-Temporal VAE Approach for Traffic Data Imputation
Jiayuan Chen ... Xiaofei Chen
-
Jiayuan Chen, et. al.Jiayuan Chen ... Xiaofei Chen
01 Jan 2020
Traffic Data Imputation Algorithm Based on Improved Low-Rank Matrix Decomposition
Xianglong Luo ... Yonghong Chen
Journal of Sensors | VOL. 2019
Xianglong Luo, et. al.Xianglong Luo ... Yonghong Chen
01 Jul 2019
Traffic Missing Data Imputation: A Selective Overview of Temporal Theories and Algorithms
Tuo Sun ... Ruochen Hao
Mathematics | VOL. 10
Tuo Sun, et. al.Tuo Sun ... Ruochen Hao
21 Jul 2022
View more papers

More From: Applied Soft Computing

Paper Title
Journal
Date
Author
An enhanced secondary decomposition model considering energy price for carbon price prediction
Gen Deng ... Youjie Li
Applied Soft Computing | VOL. 170
Gen Deng, et. al.Gen Deng ... Youjie Li
01 Feb 2025
Dynamic Q&A multi-label classification based on adaptive multi-scale feature extraction
Ying Li ... Jin Ding
Applied Soft Computing | VOL. 170
Ying Li, et. al.Ying Li ... Jin Ding
01 Feb 2025
Emotional classification in COVID-19: Analyzing Chinese microblogs with domain-adapted contrastive learning
Nankai Lin ... Lianxi Wang
Applied Soft Computing | VOL. -
Nankai Lin, et. al.Nankai Lin ... Lianxi Wang
01 Feb 2025
Evolutionary induced survival trees for medical prognosis assessment
Malgorzata Kretowska ... Marek Kretowski
Applied Soft Computing | VOL. 170
Malgorzata Kretowska, et. al.Malgorzata Kretowska ... Marek Kretowski
01 Feb 2025
View more papers

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.