[HTML][HTML] Migratable urban street scene sensing method based on vision language pre-trained model
We propose a geographically reproducible approach to urban scene sensing based on
large-scale pre-trained models. With the rise of GeoAI research, many high-quality urban …
large-scale pre-trained models. With the rise of GeoAI research, many high-quality urban …
Ginar: An end-to-end multivariate time series forecasting model suitable for variable missing
Multivariate time series forecasting (MTSF) is crucial for decision-making to precisely
forecast the future values/trends, based on the complex relationships identified from …
forecast the future values/trends, based on the complex relationships identified from …
Missing traffic data imputation for artificial intelligence in intelligent transportation systems: review of methods, limitations, and challenges
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 …
Multi-view dynamic graph convolution neural network for traffic flow prediction
The rapid urbanization and continuous improvement of road traffic equipment result in
massive daily production of traffic data. These data contain the long-term evolution of traffic …
massive daily production of traffic data. These data contain the long-term evolution of traffic …
Knowledge and topology: A two layer spatially dependent graph neural networks to identify urban functions with time-series street view image
With the rise of GeoAI research, streetscape imagery has received extensive attention due to
its comprehensive coverage, abundant information, and accessibility. However, obtaining a …
its comprehensive coverage, abundant information, and accessibility. However, obtaining a …
City2vec: Urban knowledge discovery based on population mobile network
Due to the needs of social and economic development, population movements between
cities often occur on a large scale. Spontaneous population movements between cities …
cities often occur on a large scale. Spontaneous population movements between cities …
An intelligent deep learning framework for traffic flow imputation and short-term prediction based on dynamic features
The accurate prediction of traffic flow has emerged as a focal point in the cutting-edge
sphere of intelligent transportation. Extant methodologies rely on deep learning for short …
sphere of intelligent transportation. Extant methodologies rely on deep learning for short …
A hybrid data-driven framework for spatiotemporal traffic flow data imputation
An accurate estimation of missing data in traffic flow is crucial in urban planning, intelligent
transportation, economic geography, and other fields. Thus, improving the data quality of …
transportation, economic geography, and other fields. Thus, improving the data quality of …
Inferring intercity freeway truck volume from the perspective of the potential destination city attractiveness
Accurately inferring the spatiotemporal distribution of freeway traffic volume is one of the
bottleneck problems for intelligent management of ground transportation. Although the …
bottleneck problems for intelligent management of ground transportation. Although the …
Urban traffic flow prediction: A dynamic temporal graph network considering missing values
Accurate traffic flow prediction on the urban road network is an indispensable function of
Intelligent Transportation Systems (ITS), which is of great significance for urban traffic …
Intelligent Transportation Systems (ITS), which is of great significance for urban traffic …