@article{1469745,
      note = {Includes index.},
      author = {Manshahia, Mukhdeep Singh, and Kharchenko, Valeriy, and  Weber, Gerhard-Wilhelm, and Vasant, Pandian,},
      url = {http://library.usi.edu/record/1469745},
      title = {Advances in artificial intelligence for renewable energy  systems and energy autonomy /},
      abstract = {This book provides readers with emerging research that  explores the theoretical and practical aspects of  implementing new and innovative artificial intelligence  (AI) techniques for renewable energy systems. The  contributions offer broad coverage on economic and  promotion policies of renewable energy and  energy-efficiency technologies, the emerging fields of  neuro-computational models and simulations under  uncertainty (such as fuzzy-based computational models and  fuzzy trace theory), evolutionary computation,  metaheuristics, machine learning applications, advanced  optimization, and stochastic models. This book is a pivotal  reference for IT specialists, industry professionals,  managers, executives, researchers, scientists, and  engineers seeking current research in emerging perspectives  in artificial intelligence, renewable energy systems, and  energy autonomy. Based on sustainability as a fundamental  factor for intelligent computing; Focuses on the role AI  plays in smart living, energy transition, and sustainable  development; Covers a broad range of green energy-related  topics.},
      doi = {https://doi.org/10.1007/978-3-031-26496-2},
      recid = {1469745},
      pages = {1 online resource (xxii, 285 pages) :},
}