Energy Conversion Systems-Based Artificial Intelligence (Hardcover)
Langue : anglais
Edité par Springer Nature Switzerland AG, Cham, 2025
- Livre relié
- Neuf

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Ajouter au panierA propos de cet article
Hardcover. This book aims to propose advanced solutions based on artificial intelligence techniques for ECS in order to increase energy efficiency, ensure the safety of the ECS, and to improve the quality of the energy supplied to the grid. The efficiency and quality of the electrical energy produced depends mainly on the structure and efficiency of the control technology developed for the Energy Conversion System (ECS). To improve the performance of ECSs, it is interesting to design control systems that emulate some functions performed by the human brain. Among these interesting functions are self-adaptation, learning, flexibility of operation and planning in the presence of large uncertainties and with minimal information. Based on these aspects, artificial intelligence (AI) techniques can be developed and applied to solve the different control problems of ECSs.For academics, professionals, practitioners, and graduate students interested in the most recent research on the application of AI in ECS, it is the ideal reference source. This book aims to propose advanced solutions based on artificial intelligence techniques for ECS in order to increase energy efficiency, ensure the safety of the ECS, and to improve the quality of the energy supplied to the grid. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
N° de réf. du vendeur 9789819626649
- Titre
- Energy Conversion Systems-Based Artificial Intelligence (Hardcover)
- Auteur
- Mahmoud A. Mossa
- Éditeur
- Springer Nature Switzerland AG, Cham
- Année de publication
- 2025
- État de l'article
- new
- Reliure
- Hardcover
- Langue
- anglais
- ISBN à 10 chiffres
- 9819626641
- ISBN à 13 chiffres
- 9789819626649
This book aims to propose advanced solutions based on artificial intelligence techniques for ECS in order to increase energy efficiency, ensure the safety of the ECS, and to improve the quality of the energy supplied to the grid. The efficiency and quality of the electrical energy produced depends mainly on the structure and efficiency of the control technology developed for the Energy Conversion System (ECS). To improve the performance of ECSs, it is interesting to design control systems that emulate some functions performed by the human brain. Among these interesting functions are self-adaptation, learning, flexibility of operation and planning in the presence of large uncertainties and with minimal information. Based on these aspects, artificial intelligence (AI) techniques can be developed and applied to solve the different control problems of ECSs.
For academics, professionals, practitioners, and graduate students interested in the most recent research on the application of AI in ECS, it is the ideal reference source.
« Synopsis » peut appartenir à une autre édition de cet ouvrage.
À propos de l’auteur
Dr. Mahmoud A. Mossa graduated and received his Bachelor's and Master's degrees in Electrical Engineering from the Faculty of Engineering at Minia University--Egypt in 2008 and 2013, respectively. Since January 2010, he has been working as an assistant lecturer at the Electrical Engineering Department at the same university. In November 2014, he joined the Electric Drives Laboratory (EDLAB) at the University of Padova in Italy for his Ph.D. research activities. In April 2018, he was awarded the Ph.D. degree in Electrical Engineering from the University of Padova. Since May 2018, he has been working as an assistant professor at the Electrical Engineering Department at Minia University in Egypt. He was a postdoctoral fellow at the Department of Industrial Engineering at the University of Padova in Italy for six months starting in October 2021.
Dr. Najib El Ouanjli is currently a Professor at the Electrical Engineering Department at the "Higher School of Technology, Moulay Ismail University, Meknes, Morocco". He received his Ph.D. degree in 2021 from "Sidi Mohammed Ben Abdellah University, Higher School of Technology, Fez, Morocco" and his Master's Degree in 2015 from the "Faculty of Sciences Dhar El Mahraz, Fez, Morocco". He was a professor of the Physics Science Ministry of Education from 2013 to 2021. His research interests are focused on renewable energy systems, electrical and electronics engineering, Rotating Electric Machines, System Modeling, Control Techniques, Optimization Techniques, Fault Diagnosis, Wind Turbines, and Solar Energy. He has published over several publications (international journals, book chapters, and conferences/workshops).
Dr. Mariya Ouaissa is currently a professor at the Institute Specializing in New Information and Communication Technologies, a researcher associate, and a practitioner with industry and academic experience. She is a Ph.D. graduate in 2019 in Computer Science and Networks, at the Laboratory of Modelisation of Mathematics and Computer Science from ENSAM-Moulay Ismail University, Meknes, Morocco. She has served and continues to serve on technical program and organizer committees of several conferences and events and has organized many symposiums/workshops/conferences as a general chair and also as a reviewer of numerous international journals. Dr. Ouaissa has made contributions in the fields of information security and privacy, Internet of things security, and wireless and constrained network security. Her main research topics are IoT, M2M, D2D, WSN, cellular networks, and vehicular networks.
Dr. Mariyam Ouaissa is currently a professor at the Institute specializing in new information and communication technologies, a researcher associate, and a consultant trainer in Computer Science and Networks. She received her Ph.D. degree in 2019 from the National Graduate School of Arts and Crafts, Meknes, Morocco. She is a communication and networking researcher and practitioner with industry and academic experience. Dr. Ouaissa's research is multidisciplinary and focuses on the Internet of Things, M2M, WSN, vehicular communications and cellular networks, security networks, congestion overload problems, and resource allocation management and access control. She has published more than 30 research papers (this includes book chapters, peer-reviewed journal articles, and peer-reviewed conference manuscripts), 8 edited books, and 6 special issues as a guest editor. She has served on program committees and organizing committees of several conferences and events and has organized many symposiums/workshops/conferences as a general chair.
Dr. Rajesh Kumar Dhanaraj, a distinguished Professor at Symbiosis International University, Pune, India, previously held the same title at Galgotias University, Greater Noida. Recognized among the top 2% of global scientists by Elsevier and Stanford University, he holds a Ph.D. in Computer Science and Engineering from Anna University, Chennai. With over 80 authored and edited books, 27 patents, and 170 articles, his research expertise spans Machine Learning, Cyber-Physical Systems, and Wireless Sensor Networks. As a Senior IEEE Member, he fosters global collaborations, delivers tech talks, and serves on editorial boards for prestigious journals like Elsevier and Hindawi. Furthermore, his role extends to advising Texas Instruments Inc., USA, as an Expert Advisory Panel Member.
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