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Applications of Deep Machine Learning in Future Energy Systems

Applications of Deep Machine Learning in Future Energy Systems
Applications of Deep Machine Learning in Future Energy Systems

Applications of Deep Machine Learning in Future Energy Systems

Paperback | Engels
  • Nog niet verschenen, verwacht op 4 jul. 2024
  • Niet op voorraad in onze winkel
€ 187,50
  • Vanaf €15,- geen verzendkosten.
  • 30 dagen ruiltermijn voor fysieke producten

Omschrijving

Dr. Mohammad-Hassan Khooban is an Assistant Professor in the Department of Engineering and the Director of the Power Circuits and Systems Research Group at Aarhus University in Denmark. He has authored or co-authored more than 220 publications in peer-reviewed journals (mostly IEEE) and international conferences, written three book chapters, and holds one patent. He has been involved in six national and international projects. He was identified in 2019, 2020, and 2021 by Stanford University as one of the world’s top 2% researchers in engineering. He was also ranked 16th in the list of top 30 Electronics and Electrical Engineering Scientists in Denmark in 2022. His research interests include the application of advanced control, and optimization of artificial intelligence-inspired techniques in power electronics and systems.

Dr. Mohammad-Hassan Khooban is an Assistant Professor in the Department of Engineering and the Director of the Power Circuits and Systems Research Group at Aarhus University in Denmark. He has authored or co-authored more than 220 publications in peer-reviewed journals (mostly IEEE) and international conferences, written three book chapters, and holds one patent. He has been involved in six national and international projects. He was identified in 2019, 2020, and 2021 by Stanford University as one of the world’s top 2% researchers in engineering. He was also ranked 16th in the list of top 30 Electronics and Electrical Engineering Scientists in Denmark in 2022. His research interests include the application of advanced control, and optimization of artificial intelligence-inspired techniques in power electronics and systems.

Specificaties

  • Uitgever
    Elsevier - Health Sciences Division
  • Verschenen
    jul. 2024
  • Bladzijden
    250
  • Genre
    Elektrotechniek
  • Afmetingen
    229 x 151 mm
  • EAN
    9780443214325
  • Paperback
    Paperback
  • Taal
    Engels

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