Artificial Neural Networks for Renewable Energy Systems and Manufacturing Applications Books

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Artificial Neural Networks for Renewable Energy Systems and Real World Applications


Artificial Neural Networks for Renewable Energy Systems and Real World Applications
  • Author : Ammar Hamed Elsheikh
  • Publisher : Academic Press
  • Release : 2021-06-15
  • ISBN : 0128207930
  • Language : En, Es, Fr & De
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Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modelling, analysis, and optimization of different energy systems and manufacturing processes. The applications of Artificial Neural Networks (ANN) in different engineering disciplines have attracted the attention of researchers to solve complex engineering problems that cannot be solved through conventional methods. 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 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 system and manufacturing process analysis. Includes illustrative examples of 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 Neural Networks for Renewable Energy Systems and Real World Applications


Artificial Neural Networks for Renewable Energy Systems and Real World Applications
  • Author : Ammar Hamed Elsheikh
  • Publisher : Academic Press
  • Release : 2021-06-01
  • ISBN : 9780128231869
  • Language : En, Es, Fr & De
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Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modelling, analysis, and optimization of different energy systems and manufacturing processes. The applications of Artificial Neural Networks (ANN) in different engineering disciplines have attracted the attention of researchers to solve complex engineering problems that cannot be solved through conventional methods. 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 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 system and manufacturing process analysis. Includes illustrative examples of 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


Artificial Intelligence in Energy and Renewable Energy Systems
  • Author : Soteris Kalogirou
  • Publisher : Nova Publishers
  • Release : 2007
  • ISBN : 1600212611
  • Language : En, Es, Fr & De
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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.

Soft Computing in Green and Renewable Energy Systems


Soft Computing in Green and Renewable Energy Systems
  • Author : Kasthurirangan Gopalakrishnan
  • Publisher : Springer
  • Release : 2011-08-20
  • ISBN : 9783642221767
  • Language : En, Es, Fr & De
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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.

Application of Geographical Information Systems and Soft Computation Techniques in Water and Water Based Renewable Energy Problems


Application of Geographical Information Systems and Soft Computation Techniques in Water and Water Based Renewable Energy Problems
  • Author : Mrinmoy Majumder
  • Publisher : Springer
  • Release : 2017-09-18
  • ISBN : 9789811062056
  • Language : En, Es, Fr & De
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This book highlights the application of Geographical Information System (GIS) and nature based algorithms to solve the problems of water and water based renewable energy resources. The irregularity in availability of resources and inefficiency in utilization of the available resources has reduced the potentiality of water and water based renewable energy resources. In recent years various soft computation methods (SCM) along with GIS were adopted to solve critical problems. The book collects various studies where many SCMs were used along with GIS to provide a solution for optimal utilization of natural resources for satisfying the basic needs of the population as well as fulfilling their burgeoning energy demands. The articles depict innovative application of soft computation techniques to identify the root cause and to mitigate the uncertainty for optimal utilization of the available water resources. The advantage of SCM and GIS were used to maximize the utilization of water resources under cost and time constraints in face of climatic abnormalities and effect of rapid urbanization.