Federated Learning for Early Prediction of EV Charging Demand
Fuente:
arXiv
Guardado en:
| Autores principales: | Perifanis, Vasilis, Nikolaidou, Foteini, Pavlidis, Nikolaos, Thomakos, Panagiotis, Sendros, Andreas |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic Prediction
por: Tsiolakis, Theodoros, et al.
Publicado: (2024)
por: Tsiolakis, Theodoros, et al.
Publicado: (2024)
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting
por: Pavlidis, Nikolaos, et al.
Publicado: (2024)
por: Pavlidis, Nikolaos, et al.
Publicado: (2024)
Large Language Models as Universal Predictors? An Empirical Study on Small Tabular Datasets
por: Pavlidis, Nikolaos, et al.
Publicado: (2025)
por: Pavlidis, Nikolaos, et al.
Publicado: (2025)
Improving Early Sepsis Onset Prediction Through Federated Learning
por: Düsing, Christoph, et al.
Publicado: (2025)
por: Düsing, Christoph, et al.
Publicado: (2025)
Data-Driven Optimization of EV Charging Station Placement Using Causal Discovery
por: Junker, Julius Stephan, et al.
Publicado: (2025)
por: Junker, Julius Stephan, et al.
Publicado: (2025)
Chargax: A JAX Accelerated EV Charging Simulator
por: Ponse, Koen, et al.
Publicado: (2025)
por: Ponse, Koen, et al.
Publicado: (2025)
To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
por: Bosello, Michael, et al.
Publicado: (2021)
por: Bosello, Michael, et al.
Publicado: (2021)
A Multi-View Multi-Timescale Hypergraph-Empowered Spatiotemporal Framework for EV Charging Forecasting
por: Li, Jinhao, et al.
Publicado: (2025)
por: Li, Jinhao, et al.
Publicado: (2025)
A Safe Deep Reinforcement Learning Approach for Energy Efficient Federated Learning in Wireless Communication Networks
por: Koursioumpas, Nikolaos, et al.
Publicado: (2023)
por: Koursioumpas, Nikolaos, et al.
Publicado: (2023)
Enabling Delayed-Full Charging Through Transformer-Based Real-Time-to-Departure Modeling for EV Battery Longevity
por: Lee, Yonggeon, et al.
Publicado: (2025)
por: Lee, Yonggeon, et al.
Publicado: (2025)
Exploring Energy Landscapes for Minimal Counterfactual Explanations: Applications in Cybersecurity and Beyond
por: Evangelatos, Spyridon, et al.
Publicado: (2025)
por: Evangelatos, Spyridon, et al.
Publicado: (2025)
Learning from Yesterday's Error: An Efficient Online Learning Method for Traffic Demand Prediction
por: Huang, Xiannan, et al.
Publicado: (2026)
por: Huang, Xiannan, et al.
Publicado: (2026)
Learning for Interval Prediction of Electricity Demand: A Cluster-based Bootstrapping Approach
por: Dube, Rohit, et al.
Publicado: (2023)
por: Dube, Rohit, et al.
Publicado: (2023)
Anomaly Detection in Electric Vehicle Charging Stations Using Federated Learning
por: C, Bishal K, et al.
Publicado: (2025)
por: C, Bishal K, et al.
Publicado: (2025)
Early prediction of the risk of ICU mortality with Deep Federated Learning
por: Randl, Korbinian, et al.
Publicado: (2022)
por: Randl, Korbinian, et al.
Publicado: (2022)
Predicting Long Term Sequential Policy Value Using Softer Surrogates
por: Nam, Hyunji, et al.
Publicado: (2024)
por: Nam, Hyunji, et al.
Publicado: (2024)
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
por: Jin, Jikai, et al.
Publicado: (2023)
por: Jin, Jikai, et al.
Publicado: (2023)
Enhancing Performance for Highly Imbalanced Medical Data via Data Regularization in a Federated Learning Setting
por: Tsoumplekas, Georgios, et al.
Publicado: (2024)
por: Tsoumplekas, Georgios, et al.
Publicado: (2024)
A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction
por: Chao, Wenshuo, et al.
Publicado: (2024)
por: Chao, Wenshuo, et al.
Publicado: (2024)
An Architecture Built for Federated Learning: Addressing Data Heterogeneity through Adaptive Normalization-Free Feature Recalibration
por: Siomos, Vasilis, et al.
Publicado: (2024)
por: Siomos, Vasilis, et al.
Publicado: (2024)
Early Prediction of Sepsis: Feature-Aligned Transfer Learning
por: Komolafe, Oyindolapo O., et al.
Publicado: (2025)
por: Komolafe, Oyindolapo O., et al.
Publicado: (2025)
CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee
por: Yang, Chao, et al.
Publicado: (2025)
por: Yang, Chao, et al.
Publicado: (2025)
Origin-Destination Demand Prediction: An Urban Radiation and Attraction Perspective
por: Ma, Xuan, et al.
Publicado: (2024)
por: Ma, Xuan, et al.
Publicado: (2024)
Predicting Survival of Hemodialysis Patients using Federated Learning
por: Raju, Abhiram, et al.
Publicado: (2024)
por: Raju, Abhiram, et al.
Publicado: (2024)
Federated Graph Learning for EV Charging Demand Forecasting with Personalization Against Cyberattacks
por: Li, Yi, et al.
Publicado: (2024)
por: Li, Yi, et al.
Publicado: (2024)
Improving Operational Efficiency In EV Ridepooling Fleets By Predictive Exploitation of Idle Times
por: Provoost, Jesper C., et al.
Publicado: (2022)
por: Provoost, Jesper C., et al.
Publicado: (2022)
Applied Federated Model Personalisation in the Industrial Domain: A Comparative Study
por: Siniosoglou, Ilias, et al.
Publicado: (2024)
por: Siniosoglou, Ilias, et al.
Publicado: (2024)
FedPoP: Federated Learning Meets Proof of Participation
por: İşler, Devriş, et al.
Publicado: (2025)
por: İşler, Devriş, et al.
Publicado: (2025)
Blockchain Federated Learning for Sustainable Retail: Reducing Waste through Collaborative Demand Forecasting
por: Turazza, Fabio, et al.
Publicado: (2026)
por: Turazza, Fabio, et al.
Publicado: (2026)
A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting
por: Park, Young-Jin, et al.
Publicado: (2024)
por: Park, Young-Jin, et al.
Publicado: (2024)
A Deep Learning Framework for Heat Demand Forecasting using Time-Frequency Representations of Decomposed Features
por: Ramachandran, Adithya, et al.
Publicado: (2026)
por: Ramachandran, Adithya, et al.
Publicado: (2026)
Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction
por: Antico, Thalita Mendonça, et al.
Publicado: (2024)
por: Antico, Thalita Mendonça, et al.
Publicado: (2024)
Angular Regularization for Positive-Unlabeled Learning on the Hypersphere
por: Sevetlidis, Vasileios, et al.
Publicado: (2025)
por: Sevetlidis, Vasileios, et al.
Publicado: (2025)
Preference Learning with Response Time: Robust Losses and Guarantees
por: Sawarni, Ayush, et al.
Publicado: (2025)
por: Sawarni, Ayush, et al.
Publicado: (2025)
A Comparative Study of Machine Learning Techniques for Early Prediction of Diabetes
por: Alzboon, Mowafaq Salem, et al.
Publicado: (2025)
por: Alzboon, Mowafaq Salem, et al.
Publicado: (2025)
Consistency of Neural Causal Partial Identification
por: Tan, Jiyuan, et al.
Publicado: (2024)
por: Tan, Jiyuan, et al.
Publicado: (2024)
Evaluating the Energy Efficiency of NPU-Accelerated Machine Learning Inference on Embedded Microcontrollers
por: Fanariotis, Anastasios, et al.
Publicado: (2025)
por: Fanariotis, Anastasios, et al.
Publicado: (2025)
Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning
por: Ma, Hui, et al.
Publicado: (2025)
por: Ma, Hui, et al.
Publicado: (2025)
Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning
por: Chandrinos, Nikolaos, et al.
Publicado: (2024)
por: Chandrinos, Nikolaos, et al.
Publicado: (2024)
Neurosymbolic AI for Travel Demand Prediction: Integrating Decision Tree Rules into Neural Networks
por: Acharya, Kamal, et al.
Publicado: (2025)
por: Acharya, Kamal, et al.
Publicado: (2025)
Ejemplares similares
-
Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic Prediction
por: Tsiolakis, Theodoros, et al.
Publicado: (2024) -
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting
por: Pavlidis, Nikolaos, et al.
Publicado: (2024) -
Large Language Models as Universal Predictors? An Empirical Study on Small Tabular Datasets
por: Pavlidis, Nikolaos, et al.
Publicado: (2025) -
Improving Early Sepsis Onset Prediction Through Federated Learning
por: Düsing, Christoph, et al.
Publicado: (2025) -
Data-Driven Optimization of EV Charging Station Placement Using Causal Discovery
por: Junker, Julius Stephan, et al.
Publicado: (2025)