Applications of Big Data and Artificial Intelligence in Smart Energy Systems Volume 1 Smart Energy System: Design and Its State-Of-the Art Technologies.

This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management.

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Bibliographic Details
Other Authors: Nagpal, Neelu., Alhelou, Hassan Haes, 1988-, Siano, Pierluigi., Sanjeevikumar, Padmanaban, 1978-, Lakshmi, D.
Format: Electronic
Language: English
Published: Milton : River Publishers, 2023.
Series: River Publishers Series in Computing and Information Science and Technology Series.
Subjects:
Smart power grids.
Big data > Industrial applications.
Artificial intelligence > Industrial applications.
elektronické knihy
electronic books
ISBN: 1000963837
9781003440710
1003440711
9781000963823
1000963829
9788770228244
8770228248
9781000963830
8770228256
9788770228251
Physical Description: 1 online resource (318 p.).

Cover

Table of contents

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245 0 0 |a Applications of Big Data and Artificial Intelligence in Smart Energy Systems  |h [electronic resource] :  |b Volume 1 Smart Energy System: Design and Its State-Of-the Art Technologies. 
246 3 0 |a Smart energy system 
260 |a Milton :  |b River Publishers,  |c 2023. 
300 |a 1 online resource (318 p.). 
490 1 |a River Publishers Series in Computing and Information Science and Technology Series 
500 |a Description based upon print version of record. 
505 0 |a Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- List of Figures -- List of Tables -- List of Contributors -- List of Abbreviations -- Chapter 1: Introduction to Smart Energy Systems in Recent Trends -- 1.1: Introduction -- 1.2: Global Emission -- 1.3: Evolution for Clean Energy: A Transition -- 1.4: Smart Energy System -- 1.5: Internet of Things (IoT) for Smart and Sustainable Future -- 1.5.1: IoT in smart city -- 1.5.2: IoT in agriculture -- 1.5.3: IoT in healthcare -- 1.5.4: IoT in smart grid and power management system 
505 8 |a 1.6: Recent Developments in Smart Energy Systems -- 1.7: Conclusion and Future Measures to be Considered -- Chapter 2: An Overview of Artificial Intelligence, Big Data, and Internet of Things for Future Energy Systems -- 2.1: Introduction -- 2.2: Related Work -- 2.3: Sectors Involved in Energy Need Big Data, AI, and IoT -- 2.3.1: The energy sector requires big data -- 2.3.2: Big data techniques -- 2.3.3: Data communication techniques -- 2.3.4: Techniques for analyzing data -- 2.3.5: Data analytics techniques in smart grid -- 2.3.6: Mining data from a power system 
505 8 |a 2.3.7: Modern grid systems and power consumption advanced analytics -- 2.4: Supporting Power Usage with IoT and Artificial Intelligence -- 2.4.1: The need for artificial intelligence in the renewable energy industry -- 2.4.2: Artificial intelligence (AI) research techniques classification -- 2.4.2.1: The use of computer-assisted learning systems -- 2.4.2.2: Fuzzy logic -- 2.4.2.3: Computer-aided translation -- 2.4.2.4: Robotics -- 2.4.2.5: Need of robotics in the energy sector -- 2.4.3: The energy sector requires IoT -- 2.5: Role of IoT in Energy Sectors 
505 8 |a 2.5.1: IoT Impacts for the energy sector -- 2.5.2: Internet of Things applications in energy policy, economics, and production -- 2.5.2.1: Sectors of regulation and the market -- 2.5.2.2: Energy supply sector -- 2.5.2.3: Power transmission grids or energy grids -- 2.5.2.4: Energy demand sector -- 2.6: Future Energy Systems' Unsolved Problems -- 2.6.1: IoT energy sector challenges -- 2.6.2: Open challenges in AI energy sector -- 2.6.3: Open data analytics challenges in energy -- 2.7: Conclusion -- Chapter 3: LoRa: A New Technology for Smart Grid Applications -- 3.1: Introduction 
505 8 |a 3.2: Related Work and Background -- 3.3: LoRa Challenges -- 3.4: LoRa Applications -- 3.5: Characteristics and Future Direction of LoRa Technology -- 3.5.1: Communication Range: -- 3.5.2: Placement of Multiple Gateways: -- 3.5.3: Link Coordination: -- 3.5.4: Security -- 3.5.5: Big data and AI -- 3.6: Case Study -- 3.7: Conclusion -- Chapter 4: Clustering Hybrid Application for Load Forecasting in Smart Grids -- 4.1: Introduction -- 4.1.1: Dataset pre-processing -- 4.1.2: Clustering techniques -- 4.1.2.1: K-means -- 4.1.2.2: Partitioning around medoids (PAM) 
500 |a 4.1.2.3: Gaussian mixture model (GMM) 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book covers the applications of various big data analytics, artificial intelligence, and machine learning technologies in smart grids for demand prediction, decision-making processes, policy, and energy management. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Smart power grids. 
650 0 |a Big data  |x Industrial applications. 
650 0 |a Artificial intelligence  |x Industrial applications. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Nagpal, Neelu. 
700 1 |a Alhelou, Hassan Haes,  |d 1988- 
700 1 |a Siano, Pierluigi. 
700 1 |a Sanjeevikumar, Padmanaban,  |d 1978- 
700 1 |a Lakshmi, D. 
776 0 8 |i Print version:  |a Nagpal, Neelu  |t Applications of Big Data and Artificial Intelligence in Smart Energy Systems  |d Milton : River Publishers,c2023  |z 9788770228251 
830 0 |a River Publishers Series in Computing and Information Science and Technology Series. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpABDAISE4/applications-of-big?kpromoter=marc  |y Full text 

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