HOME Popular Books Popular Audioooks Popular Textbooks Popular Freebooks More Genres

Book

Audiobook

Genres

Computer Vision and Machine Intelligence for Renewable Energy Systems

By Ashutosh Kumar Dubey, Abhishek Kumar, Umesh Chandra Pati, Fausto Pedro García Marquez, Vicente García-Díaz & Arun Lal Srivastav

Release : 2024-09-20

Genre : Power Resources, Books, Professional & Technical, Engineering, Electrical Engineering

Kind : ebook

(0 ratings)
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.
This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered.
The very first book in Elsevier’s cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systemsBuilds knowledge and tools in a systematic manner, from fundamentals to advanced applicationsIncludes dedicated chapters with case studies and applications for each sustainable energy source

Computer Vision and Machine Intelligence for Renewable Energy Systems

By Ashutosh Kumar Dubey, Abhishek Kumar, Umesh Chandra Pati, Fausto Pedro García Marquez, Vicente García-Díaz & Arun Lal Srivastav

Release : 2024-09-20

Genre : Power Resources, Books, Professional & Technical, Engineering, Electrical Engineering

Kind : ebook

(0 ratings)
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.
This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered.
The very first book in Elsevier’s cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids.Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systemsBuilds knowledge and tools in a systematic manner, from fundamentals to advanced applicationsIncludes dedicated chapters with case studies and applications for each sustainable energy source

advertisement

Access e-books

More By Ashutosh Kumar Dubey, Abhishek Kumar, Umesh Chandra Pati, Fausto Pedro García Marquez, Vicente García-Díaz & Arun Lal Srivastav

Blockchain, Artificial Intelligence, and the Internet of Things

Computer Vision and Machine Intelligence for Renewable Energy Systems

AI and IoT-Based Intelligent Automation in Robotics

Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence

Interdisciplinary Engineering Sciences

Machine Learning Approaches and Applications in Applied Intelligence for Healthcare Data Analytics

Artificial Intelligence for Renewable Energy systems (Enhanced Edition)

Sustainable Management of Electronic Waste