6 papers
Electric Vehicle Charging Load Forecasting: An Experimental Comparison of Machine Learning Methods
Iason Kyriakopoulos, Yannis Theodoridis
With the growing popularity of electric vehicles as a means of addressing climate change, concerns have emerged regarding their impact on electric grid management. As a result, pre…
Towards Data-driven Nitrogen Estimation in Wheat Fields using Multispectral Images
Andreas Tritsarolis, Tomaž Bokan, Matej Brumen +2
The modernization of agriculture has motivated the development of advanced analytics and decision-support systems to improve resource utilization and reduce environmental impacts.…
On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning
Andreas Tritsarolis, Gil Sampaio, Nikos Pelekis +1
The wide spread of new energy resources, smart devices, and demand side management strategies has motivated several analytics operations, from infrastructure load modeling to user…
Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting
Antonios Tziorvas, Andreas Tritsarolis, Yannis Theodoridis
The rapid growth of dockless bike-sharing systems has generated massive spatio-temporal datasets useful for fleet allocation, congestion reduction, and sustainable mobility. Bike d…
MoDE-Boost: Boosting Shared Mobility Demand with Edge-Ready Prediction Models
Antonios Tziorvas, George S. Theodoropoulos, Yannis Theodoridis
Urban demand forecasting plays a critical role in optimizing routing, dispatching, and congestion management within Intelligent Transportation Systems. By leveraging data fusion an…
FLP-XR: Future Location Prediction on Extreme Scale Maritime Data in Real-time
George S. Theodoropoulos, Andreas Patakis, Andreas Tritsarolis +1
Movements of maritime vessels are inherently complex and challenging to model due to the dynamic and often unpredictable nature of maritime operations. Even within structured marit…