Add to ORKGTraffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objective of this master thesis is to perform traffic forecasting in urban contexts by developing machine learning models trained with simulated Floating Car Data
The term deep learning-based framework for smart mobility refers to a concept or research article th...
The capability of traffic-information systems to sense the movement of millions of users and offer t...
The Intelligent transportation system is essential to build smarter cities. Machine learning based t...
Traffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objec...
Traffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objec...
This paper, titled "Revolutionizing Urban Mobility," focuses on data-driven traffic forecasting and ...
This master thesis deals with the problem of traffic forecasting using probe vehicle data on freeway...
In the past few years, Deep learning has re-emerged as a powerful tool to solve complex problems and...
This study attempts to develop a model that forecasts precise data on traffic flow. Everything that ...
This study attempts to develop a model that forecasts precise data on traffic flow. Everything that ...
The future of smart city traffic forecasting is two-way communication between residents and the city...
Timely forecast of traffic is very much needed for smart cities, which allows travelers and governme...
Nowcasting is the prediction of the present and the very near future of an indicator. Traffic Nowcas...
Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces mo...
Traffic information is of great importance for urban cities, and accurate prediction of urban traffi...
The term deep learning-based framework for smart mobility refers to a concept or research article th...
The capability of traffic-information systems to sense the movement of millions of users and offer t...
The Intelligent transportation system is essential to build smarter cities. Machine learning based t...
Traffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objec...
Traffic forecasting plays a key role in mitigating traffic congestion in urban areas. The main objec...
This paper, titled "Revolutionizing Urban Mobility," focuses on data-driven traffic forecasting and ...
This master thesis deals with the problem of traffic forecasting using probe vehicle data on freeway...
In the past few years, Deep learning has re-emerged as a powerful tool to solve complex problems and...
This study attempts to develop a model that forecasts precise data on traffic flow. Everything that ...
This study attempts to develop a model that forecasts precise data on traffic flow. Everything that ...
The future of smart city traffic forecasting is two-way communication between residents and the city...
Timely forecast of traffic is very much needed for smart cities, which allows travelers and governme...
Nowcasting is the prediction of the present and the very near future of an indicator. Traffic Nowcas...
Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces mo...
Traffic information is of great importance for urban cities, and accurate prediction of urban traffi...
The term deep learning-based framework for smart mobility refers to a concept or research article th...
The capability of traffic-information systems to sense the movement of millions of users and offer t...
The Intelligent transportation system is essential to build smarter cities. Machine learning based t...