Machine Learning for Sustainable Energy Solutions
Sold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since 9 October 2009
New - Hardcover
Condition: New
Ships within U.S.A.
Quantity: Over 20 available
Add to basketSold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since 9 October 2009
Condition: New
Quantity: Over 20 available
Add to basket2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
Seller Inventory # V9781394267408
Comprehensive insights into integrating modern engineering techniques with machine learning and renewable energy to create a more sustainable world
Through an interdisciplinary approach, Machine Learning for Sustainable Energy Solutions provides comprehensive insights into integrating modern engineering techniques such as machine learning (ML), artificial intelligence (AI), nanotechnology, digital twins, and the Internet of Things (IoT) with renewable energy. Each chapter is based on modern research and enhanced by experimental or simulated data.
The book offers a thorough review of several energy storage techniques, helping readers fully grasp the larger background in which chemical, thermal, electrical, mechanical, and machine learning technologies may be used to evaluate, categorize, and maximize different storage systems. The book also reviews the confluence of the Internet of Things (IoT) and machine learning for real-time digestive parameter control and monitoring, along with the cooperative importance of mathematical modeling and artificial intelligence in maximizing reactor performance, gas output, and operational stability.
Machine Learning for Sustainable Energy Solutions includes information on:
Machine Learning for Sustainable Energy Solutions is an essential reference for professionals, researchers, educators, and students working in the fields of energy, environmental science, and machine learning. The book also helps decision-makers in various fields by providing them the required knowledge to make informed choices on sustainable practices and policies.
Zafar Said, PhD, is a Mechanical and Aerospace Engineering Associate Professor at UAE University. With over AED six million in research funding, he has led industry-focused projects with SEWA, Tabreed, and Masdar, advancing innovations in nanofluids, solar energy, AI, and low-carbon fuels.
Prabhakar Sharma, PhD, is an assistant professor at Delhi Skill and Entrepreneurship University, Delhi, India. He has 30 years of combined experience in academia and industry.
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