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

Ammar Hamed Elsheikh, Mohamed Abd Elaziz

• Publisher: Academic Press
• Year: 2022
• ISBN:
  9780128231869
• Topic: Technology & Engineering
• Subtopic: Renewable Power Resources
• Index: Technology & Engineering

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

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• About the editors
• Chapter one. Basics of artificial neural networks
• Chapter two. Artificial neural network applied to the renewable energy system performance
• Chapter three. Applications of artificial neural networks in concentrating solar power systems
• Chapter four. Neural simulation of a solar thermal system in low temperature
• Chapter five. Solar energy modelling and forecasting using artificial neural networks: a review, a case study, and applications
• Chapter six. Digital twin predictive maintenance strategy based on machine learning improving facility management in built environment
• Chapter seven. Artificial neural network and desalination systems
• Chapter eight. Artificial neural networks for engineering applications: a review
• Chapter nine. Incremental deep learning model for plant leaf diseases detection
• Chapter ten. Incremental learning of convolutional neural networks in bioinformatics
• Chapter eleven. Hybrid Arabic classification techniques based on naïve Bayes algorithm for multidisciplinary applications
• Index