• A Novel Smart Grid State Estimation Method Based on Neural Networks 

      Abdel-Nasser, Mohamed; Mahmoud, Karar; Kashef, Heba (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 06/2018)
      The rapid development in smart grids needs efficient state estimation methods. This paper presents a novel method for smart grid state estimation (e.g., voltages, active and reactive power loss) using artificial neural ...
    • An Improved Deep Learning Model for Electricity Price Forecasting 

      Iqbal, Rashed; Mokhlis, Hazlie; Mohd Khairuddin, Anis Salwa; Azam Muhammad, Munir (International Journal of Interactive Multimedia and Artificial Intelligence, 06/2023)
      Accurate electricity price forecasting (EPF) is important for the purpose of bidding strategies and minimizing the risk for market participants in the competitive electricity market. Besides that, EPF becomes critically ...
    • DisastDrone: A Disaster Aware Consumer Internet of Drone Things System in Ultra-Low Latent 6G Network 

      Mukherjee, Amartya; De, Debashis; Dey, Nilanjan; González-Crespo, Rubén; Herrera-Viedma, Enrique (IEEE Transactions on Consumer Electronics, 2023)
      Internet of Things application in disaster responses and management is a predominant research domain. The introduction of the consumer drones, flying ad-hoc networks, low latency 5G, and beyond 5G produce significant ...
    • Worldwide trends in energy market research 

      Salmerón-Manzano, Esther ; Alcayde, Alfredo; Manzano-Agugliaro, Francisco (Energy Services Fundamentals and Financing, 2020)
      This study examines global research on the subject of energy market in Scopus database. For this purpose, a bibliometric research has been carried out in the fields of title, abstract, and keywords. All the records obtained ...