Artificial Neural Networks for Renewable Energy Systems and Real World Applications Book

Artificial Neural Networks for Renewable Energy Systems and Real World Applications


  • Author : Ammar Hamed Elsheikh
  • Publisher : Academic Press
  • Release Date : 2022-09-08
  • Genre: Technology & Engineering
  • Pages : 290
  • ISBN 10 : 9780128231869
  • Total Read : 80
  • File Size : 13,7 Mb

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Artificial Neural Networks for Renewable Energy Systems and Real World Applications Summary:

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis. Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts Covers ANN theory for easy reference in subsequent technology specific sections

Artificial Intelligence in Energy and Renewable Energy Systems Book

Artificial Intelligence in Energy and Renewable Energy Systems


  • Author : Soteris Kalogirou
  • Publisher : Nova Publishers
  • Release Date : 2007
  • Genre: Science
  • Pages : 471
  • ISBN 10 : 1600212611
  • Total Read : 81
  • File Size : 18,6 Mb

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Artificial Intelligence in Energy and Renewable Energy Systems Summary:

This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.

Applications of AI and IOT in Renewable Energy Book

Applications of AI and IOT in Renewable Energy


  • Author : Rabindra Nath Shaw
  • Publisher : Academic Press
  • Release Date : 2022-02-15
  • Genre: Science
  • Pages : 246
  • ISBN 10 : 9780323984010
  • Total Read : 96
  • File Size : 18,5 Mb

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Applications of AI and IOT in Renewable Energy Summary:

Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. Includes future applications of AI and IOT in renewable energy Based on case studies to give each chapter real-life context Provides advances in renewable energy using AI and IOT with technical detail and data

Artificial Intelligence for Renewable Energy Systems Book

Artificial Intelligence for Renewable Energy Systems


  • Author : Ajay Kumar Vyas
  • Publisher : John Wiley & Sons
  • Release Date : 2022-03-02
  • Genre: Computers
  • Pages : 276
  • ISBN 10 : 9781119761693
  • Total Read : 68
  • File Size : 12,8 Mb

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Artificial Intelligence for Renewable Energy Systems Summary:

ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.

Soft Computing in Green and Renewable Energy Systems Book

Soft Computing in Green and Renewable Energy Systems


  • Author : Kasthurirangan Gopalakrishnan
  • Publisher : Springer
  • Release Date : 2011-08-20
  • Genre: Technology & Engineering
  • Pages : 305
  • ISBN 10 : 9783642221767
  • Total Read : 98
  • File Size : 13,9 Mb

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Soft Computing in Green and Renewable Energy Systems Summary:

Soft Computing in Green and Renewable Energy Systems provides a practical introduction to the application of soft computing techniques and hybrid intelligent systems for designing, modeling, characterizing, optimizing, forecasting, and performance prediction of green and renewable energy systems. Research is proceeding at jet speed on renewable energy (energy derived from natural resources such as sunlight, wind, tides, rain, geothermal heat, biomass, hydrogen, etc.) as policy makers, researchers, economists, and world agencies have joined forces in finding alternative sustainable energy solutions to current critical environmental, economic, and social issues. The innovative models, environmentally benign processes, data analytics, etc. employed in renewable energy systems are computationally-intensive, non-linear and complex as well as involve a high degree of uncertainty. Soft computing technologies, such as fuzzy sets and systems, neural science and systems, evolutionary algorithms and genetic programming, and machine learning, are ideal in handling the noise, imprecision, and uncertainty in the data, and yet achieve robust, low-cost solutions. As a result, intelligent and soft computing paradigms are finding increasing applications in the study of renewable energy systems. Researchers, practitioners, undergraduate and graduate students engaged in the study of renewable energy systems will find this book very useful.

AI and IOT in Renewable Energy Book

AI and IOT in Renewable Energy


  • Author : Rabindra Nath Shaw
  • Publisher : Springer Nature
  • Release Date : 2021-05-12
  • Genre: Technology & Engineering
  • Pages : 109
  • ISBN 10 : 9789811610110
  • Total Read : 62
  • File Size : 5,8 Mb

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AI and IOT in Renewable Energy Summary:

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

Applications of Nature Inspired Computing in Renewable Energy Systems Book

Applications of Nature Inspired Computing in Renewable Energy Systems


  • Author : Mohamed Arezki Mellal
  • Publisher : Engineering Science Reference
  • Release Date : 2021-12-17
  • Genre: Uncategoriezed
  • Pages : null
  • ISBN 10 : 1799885615
  • Total Read : 68
  • File Size : 19,8 Mb

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Applications of Nature Inspired Computing in Renewable Energy Systems Summary:

Renewable energy is crucial to preserve the environment. This energy involves various systems that must be optimized and assessed to provide better performance; however, the design and development of renewable energy systems remains a challenge. It is crucial to implement the latest innovative research in the field in order to develop and improve renewable energy systems. Applications of Nature-Inspired Computing in Renewable Energy Systems discusses the latest research on nature-inspired computing approaches applied to the design and development of renewable energy systems and provides new solutions to the renewable energy domain. Covering topics such as microgrids, wind power, and artificial neural networks, it is ideal for engineers, industry professionals, researchers, academicians, practitioners, teachers, and students.

Introduction to AI Techniques for Renewable Energy System Book

Introduction to AI Techniques for Renewable Energy System


  • Author : Suman Lata Tripathi
  • Publisher : CRC Press
  • Release Date : 2021-11-24
  • Genre: Technology & Engineering
  • Pages : 432
  • ISBN 10 : 9781000392456
  • Total Read : 61
  • File Size : 10,5 Mb

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Introduction to AI Techniques for Renewable Energy System Summary:

Introduction to AI techniques for Renewable Energy System Artificial Intelligence (AI) techniques play an essential role in modeling, analysis, and prediction of the performance and control of renewable energy. The algorithms used to model, control, or predict performances of the energy systems are complicated, involving differential equations, enormous computing power, and time requirements. Instead of complex rules and mathematical routines, AI techniques can learn critical information patterns within a multidimensional information domain. Design, control, and operation of renewable energy systems require a long-term series of meteorological data such as solar radiation, temperature, or wind data. Such long-term measurements are often non-existent for most of the interest locations or, wherever they are available, they suffer from several shortcomings, like inferior quality of data, and in-sufficient long series. The book focuses on AI techniques to overcome these problems. It summarizes commonly used AI methodologies in renewal energy, with a particular emphasis on neural networks, fuzzy logic, and genetic algorithms. It outlines selected AI applications for renewable energy. In particular, it discusses methods using the AI approach for prediction and modeling of solar radiation, seizing, performances, and controls of the solar photovoltaic (PV) systems. Features Focuses on a significant area of concern to develop a foundation for the implementation of renewable energy system with intelligent techniques Showcases how researchers working on renewable energy systems can correlate their work with intelligent and machine learning approaches Highlights international standards for intelligent renewable energy systems design, reliability, and maintenance Provides insights on solar cell, biofuels, wind, and other renewable energy systems design and characterization, including the equipment for smart energy systems This book, which includes real-life examples, is aimed at