Artificial Neural Network (ANN): Smart & Energy Systems Applications
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Georgia Southern University faculty member Adel El Shahat authored Artificial Neural Network (ANN): Smart & Energy Systems Applications.
Book Summary: This book proposes Artificial Neural Network (ANN) Applications for Smart grids and Energy Systems as a one of powerful artificial intelligence nonlinear regression techniques. This study is carried out to emphasize on the importance of ANN in many categories and for undergraduate, graduate students, engineers, and researchers. Artificial Neural Networks (ANNs) Technique is illustrated with its Fundamentals, Data Collection, Analysis and Processing, Structure Design, Number of Hidden Layers, Number of Hidden Units, Initializing Back-Propagation feed-forward network, Training, simulation, Weights and Bias, Testing, Derived mathematical equations and Graphical user interface. The adopted nonparametric ANN examples here are: Photovoltaic (PV) modeling, PM Synchronous m/c performance improvement, Storage Unit modeling, PV module Genetic Modeling, Petroleum Application for archie parameters estimation, dc-dc duty cycle Converter Estimation, Horizontal Axis Wind Turbines modeling and Capacitive Deionization (CDI) characteristics modeling for desalination application.