Artificial Neural Network (ANN) : Smart & Energy Systems Applications

Adel El Shahat

ISBN 10: 3639711149 / ISBN 13: 9783639711141

Published by Scholars' Press, 2014

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9783639711141

Bibliographic Details

• Title: Artificial Neural Network (ANN) : Smart & Energy Systems Applications
• Publisher: Scholars' Press
• Publication Date: 2014
• Language: English
• ISBN 10: 3639711149
• ISBN 13: 9783639711141
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 12D millimeters 220 millimeters width by 150 millimeters height by 12 millimeters depth
• Weight: 304 grams

About this title

Synopsis

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.

About the Author

Assistant Prof. Engineering Science Dept. Faculty of Petroleum & Min. Eng. Suez University, Egypt. He was Visiting Researcher, ECE Dept. Green Energy Lab, OSU, USA. His interests: Smart Grids; Electric Machines;Drives; Power Electronics; Power Systems; Control Systems; Neural Networks, Genetic. He is IEEE, ASEE,IAENG, IACSIT, SAE, EES, WASET Member