11 citations · 15 across the 8 of their papers we have counts for
8 papers
SAREF-based Ontology for Distributed AI Workflows across the Edge-Fog-Cloud Continuum
Viorica Rozina Chifu, Tudor Cioara, Vasile Ofrim +4
Nowadays semantic models provide limited support for representing distributed AI workflows and their execution across heterogeneous edge, fog, and cloud environments. Therefore, AI…
Microgrids Coalitions for Energy Market Balancing
Viorica Chifu, Cristina Bianca Pop, Tudor Cioara +1
With the integration of renewable sources in electricity distribution networks, the need to develop intelligent mechanisms for balancing the energy market has arisen. In the absenc…
Evolutionary model for energy trading in community microgrids using Hawk-Dove strategies
Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop +1
This paper proposes a decentralized model of energy cooperation between microgrids, in which decisions are made locally, at the level of the microgrid community. Each microgrid is…
A Deep Q-Learning based Smart Scheduling of EVs for Demand Response in Smart Grids
Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop +2
Economic and policy factors are driving the continuous increase in the adoption and usage of electrical vehicles (EVs). However, despite being a cleaner alternative to combustion e…
Electric Vehicles coordination for grid balancing using multi-objective Harris Hawks Optimization
Cristina Bianca Pop, Tudor Cioara, Viorica Chifu +2
The rise of renewables coincides with the shift towards Electrical Vehicles (EVs) posing technical and operational challenges for the energy balance of the local grid. Nowadays, th…
FedWOA: A Federated Learning Model that uses the Whale Optimization Algorithm for Renewable Energy Prediction
Viorica Chifu, Tudor Cioara, Cristian Anitiei +2
Privacy is important when dealing with sensitive personal information in machine learning models, which require large data sets for training. In the energy field, access to househo…
Deep Learning for Forecasting the Energy Consumption in Public Buildings
Viorica Rozina Chifu, Cristina Bianca Pop, Emil St. Chifu +1
In this paper we propose a Long Short-Term Memory Network based method to forecast the energy consumption in public buildings, based on past measurements. Our approach consists of…
Forecasting the Short-Term Energy Consumption Using Random Forests and Gradient Boosting
Cristina Bianca Pop, Viorica Rozina Chifu, Corina Cordea +2
This paper analyzes comparatively the performance of Random Forests and Gradient Boosting algorithms in the field of forecasting the energy consumption based on historical data. Th…