ST-LBAGAN: Spatio-temporal learnable bidirectional attention generative adversarial networks for missing traffic data imputation
B Yang, Y Kang, YY Yuan, X Huang, H Li - Knowledge-Based Systems, 2021 - Elsevier
Real-time, accurate and comprehensive traffic flow data is the key of intelligent
transportation systems to provide efficient services for urban transportation. In the process of …
transportation systems to provide efficient services for urban transportation. In the process of …
GAN and multi-agent DRL based decentralized traffic light signal control
Adaptive traffic light signal control (ATSC) is a promising paradigm for alleviating traffic
congestion in intelligent transportation systems. Most of the existing methods require heavy …
congestion in intelligent transportation systems. Most of the existing methods require heavy …
Towards a Framework to Evaluate Generative Time Series Models for Mobility Data Features
Understanding human mobility has implications for several areas, such as immigration,
disease control, mobile networks performance, and urban planning. However, gathering and …
disease control, mobile networks performance, and urban planning. However, gathering and …
Traffic-data recovery using geometric-algebra-based generative adversarial network
D Zang, Y Ding, X Qu, C Miao, X Chen, J Zhang… - Sensors, 2022 - mdpi.com
Traffic-data recovery plays an important role in traffic prediction, congestion judgment, road
network planning and other fields. Complete and accurate traffic data help to find the laws …
network planning and other fields. Complete and accurate traffic data help to find the laws …
[PDF][PDF] MobDeep: um arcabouço para geração de dados de mobilidade urbana utilizando aprendizado profundo
ES Vitória - sappg.ufes.br
Entender a mobilidade dos componentes de redes móveis é fundamental para diversos
tipos de redes, como redes sem fio, redes veiculares ou ad hoc. Nesse sentido, o estudo e …
tipos de redes, como redes sem fio, redes veiculares ou ad hoc. Nesse sentido, o estudo e …