Applications of Deep Machine Learning in Future Energy Systems
Home > Science, Technology & Agriculture > Energy technology and engineering > Electrical engineering > Applications of Deep Machine Learning in Future Energy Systems
Applications of Deep Machine Learning in Future Energy Systems

Applications of Deep Machine Learning in Future Energy Systems


     0     
5
4
3
2
1



Available


X
About the Book

Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation before laying out current AI approaches and limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, this book maps a practical path towards AI capable of supporting sustainable energy.

Table of Contents:
1. Introduction 2. Artificial intelligence and Machine learning in Future Energy Systems (State-of-Art, future development) Jalal Heidary 3. Digital Twins-Assisted Design of Next-Generation DC Microgrid Meysam Gheisarnejad, Maryam Homayounzadeh, Burak Yildirim 4. Deep Learning-Based Procedure for Profit Maximization of EV Charging Stations Mohammad Hassan Khooban, Peyman Razmi, MASOUMEH SEYEDYAZDI 5. Deep Frequency Control of Power Grids Under Cyber Attacks Mohammad Aghamohammadi, jalal heidary, Soroush Oshnoei 6. Application of Q-Learning in Stabilization of Multi Carrier Energy Systems Meysam Gheisarnejad, Maryam Homayounzadeh, Burak Yildirim 7. Design of Next-Generation of 5G Data Center Power Supply based on AI Mohammad Hassan Khooban, Meysam Gheisarnejad 8. Smart EV Battery Charger Based on Deep Machine Learning Mohammad Hassan Khooban, Jalil Boudjadar, Mehdi Rafiei 9. Machine learning in Talkative Power Mohammad Hassan Khooban, Zahra Ghahraman Izadi, Ali Mousavi 10. Advanced Control of Power Electronics-based Machine Learning Maryam Homayounzadeh, Meysam Gheisarnejad, Mohamadreza Homayounzade, Mohammad Hassan Khooban 11. Multi-Level Energy Management and Optimal Control System in Smart Cities Based on Deep Machine Learning Javid Ghafourian, Atefe Hedayatnia, Ahmed Al-Durra, Reza Sepehrzad

About the Author :
Dr. Mohammad-Hassan Khooban is an Assistant Professor in the Department of Engineering and the Director of the Power Circuits and Systems Research Group at Aarhus University in Denmark. He has authored or co-authored more than 220 publications in peer-reviewed journals (mostly IEEE) and international conferences, written three book chapters, and holds one patent. He has been involved in six national and international projects. He was identified in 2019, 2020, and 2021 by Stanford University as one of the world’s top 2% researchers in engineering. He was also ranked 16th in the list of top 30 Electronics and Electrical Engineering Scientists in Denmark in 2022. His research interests include the application of advanced control, and optimization of artificial intelligence-inspired techniques in power electronics and systems.


Best Sellers


Product Details
  • ISBN-13: 9780443214325
  • Publisher: Elsevier - Health Sciences Division
  • Publisher Imprint: Elsevier - Health Sciences Division
  • Height: 229 mm
  • No of Pages: 334
  • Width: 152 mm
  • ISBN-10: 0443214328
  • Publisher Date: 21 Aug 2024
  • Binding: Paperback
  • Language: English
  • Weight: 450 gr


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Applications of Deep Machine Learning in Future Energy Systems
Elsevier - Health Sciences Division -
Applications of Deep Machine Learning in Future Energy Systems
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Applications of Deep Machine Learning in Future Energy Systems

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!