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[HTML][HTML] How machine learning informs ride-hailing services: A survey
In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …
urban transportation system, which not only provide significant ease for residents' travel …
A survey of route recommendations: Methods, applications, and opportunities
Nowadays, with advanced information technologies deployed citywide, large data volumes
and powerful computational resources are intelligentizing modern city development. As an …
and powerful computational resources are intelligentizing modern city development. As an …
ESTNet: Embedded spatial-temporal network for modeling traffic flow dynamics
Accurate spatial-temporal prediction is a fundamental building block of many real-world
applications such as traffic scheduling and management, environment policy making, and …
applications such as traffic scheduling and management, environment policy making, and …
Multimodal federated learning: Concept, methods, applications and future directions
Multimodal learning mines and analyzes multimodal data in reality to better understand and
appreciate the world around people. However, how to exploit this rich multimodal data …
appreciate the world around people. However, how to exploit this rich multimodal data …
Exploring a large-scale multi-modal transportation recommendation system
The emergence of navigation applications with multi-modal trip planning services has
brought about the demand for the multi-modal transportation recommendation systems. In …
brought about the demand for the multi-modal transportation recommendation systems. In …
Kill two birds with one stone: A multi-view multi-adversarial learning approach for joint air quality and weather prediction
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Semi-supervised hierarchical recurrent graph neural network for city-wide parking availability prediction
The ability to predict city-wide parking availability is crucial for the successful development of
Parking Guidance and Information (PGI) systems. Indeed, the effective prediction of city-wide …
Parking Guidance and Information (PGI) systems. Indeed, the effective prediction of city-wide …
Joint air quality and weather prediction based on multi-adversarial spatiotemporal networks
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Multi-agent graph convolutional reinforcement learning for dynamic electric vehicle charging pricing
Electric Vehicles (EVs) have been emerging as a promising low-carbon transport target.
While a large number of public charging stations are available, the use of these stations is …
While a large number of public charging stations are available, the use of these stations is …
Multi-modal transportation recommendation with unified route representation learning
Multi-modal transportation recommendation aims to provide the most appropriate travel
route with various transportation modes according to certain criteria. After analyzing large …
route with various transportation modes according to certain criteria. After analyzing large …