Analyzing energy transition for industry 4.0-driven hybrid energy system selection with advanced neural network-used multi-criteria decision-making technique

Liu P., ETİ S., Serhat Y., Dinçer H., Gökalp Y., Ergün E., ...Daha Fazla

RENEWABLE ENERGY, cilt.232, ss.1-27, 2024 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 232
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.renene.2024.121081
  • Dergi Adı: RENEWABLE ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), CAB Abstracts, Communication Abstracts, Compendex, Environment Index, Geobase, Greenfile, Index Islamicus, INSPEC, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1-27
  • Anahtar Kelimeler: Hybrid energy projects, Renewable energy investments, Effective resource policies, Fuzzy logic, Decision-making models
  • İstanbul Medipol Üniversitesi Adresli: Evet