000			01720nam a22002537a 4500
003			CUTN
005			20250707121309.0
008			250707b |||||||| |||| 00| 0 eng d
020			_a9780367497750
041			_aEnglish
082			_223 _a621.310 _bJIN
100			_aJindal, Anish
245			_aInternet of Energy for Smart Cities : _bMachine Learning Models and Techniques / _cAnish Jindal, Neeraj Kumar & Gagangeet Singh Aujla
250			_a1st ed.
260			_aLondon : _bTaylor & Francis Ltd, _c2022.
300			_aXX, 302 Seiten : _bill.; _c15.6 x 2.34 x 23.39 cm.
505			_a1. Smart City: The Verticals of Energy Demand and Challenges. 2. Conventional Power Grid to Smart Grid. 3. Smart Grids: An Integrated Perspective. 4. Internet of Energy: Solution for Smart Cities. 5. IoE Applications for Smart Cities. 6. IoE Design Principles and Architecture. 7. Machine Learning Models for Smart Cities. 8. Machine Learning Models in Smart Cities Data-Driven Perspective. 9. Case Study 1: Machine Learning Techniques for Monitoring of PV Panel. 10. Case Study 2: Intelligent Control System for Smart Environment. 11. Pathway and Future of the IoE in Smart Cities
520			_aThe focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It helps build the technical understanding for the reader
650			_aAutomatic control engineering
650			_aCOMPUTERS / Machine Theory
700			_aKumar, Neeraj
700			_aAujla, Gagangeet Singh
942			_2ddc _cBOOKS
999			_c44836 _d44836