The goal of this book is to use expert Artificial Neural Network (ANN) to solve various science and engineering application problems and discusses current developments in solving complicated engineering problems that cannot be solved using traditional methods. The intension of the proposed book is to give an idea to the reader about the ANN, machine learning (ML) and deep learning (DL) methods for the data of hybrid nanofluids thermophysical properties, heat transfer in heat exchangers, solar powered (CSP) flash desalination, reverse osmosis desalination, biodegradability of pollutants in saline water, emerging pollutants, solid waste management, pavement materials, concrete technology, and audio spoof classification. Apart from the topics the book also covers the various ANN, ML and DL algorithms (codes) for various applications.
The aim of this textbook is to provide a complete understanding of the Artificial Neural Networks for Engineering practices discusses current developments in solving complicated engineering problems that cannot be solved using traditional methods. The approaches proposed can be used for modeling, pattern recognition, classification, forecasting, estimating, and other tasks. Readers will discover various methodologies for solving problems such as complex nonlinear systems, cellular computational networks, wastewater treatment, cyber-physical system attack detection, mechanical systems, electrical systems, biomechanical and biomedical systems, time series forecasting, biofuels, and more.