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Engineering Science Reference (An Imprint Of Igi Global)

Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications

Ai Techniques For Renewable Source Integration And Battery Charging Methods In Electric Vehicle Applications

ISBN-13: 9781668488164
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Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.


  • | Author: S. Angalaeswari, T. Deepa, L. Ashok Kumar
  • | Publisher: Engineering Science Reference (An Imprint Of Igi Global)
  • | Publication Date: Feb 03, 2023
  • | Number of Pages: 316 pages
  • | Language: English
  • | Binding: Hardcover
  • | ISBN-10: 1668488167
  • | ISBN-13: 9781668488164
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