Artificial Neural Networks (ANNs) are immensely interesting due to their capability to predict the complex system output with various input parameters. Accordingly, researchers are seeking to improve the efficiency of ANNs in predicting the various engineering problems. Therefore, in the present book, we tried to develop an iterative methodology based on the ANNs in order to predict the engineering problems. Then, we tested this suggested method on different CFD and experimental marine engineering problems. This book highlighted the theoretical aspects of artificial neural networks (ANNs) and an iterative optimized ANN methodology. Afterward, in this book, the proposed ANN methodology is applied to various CFD and experimental marine engineering problems such as thermophysical properties of liquid water, hydrodynamics of hydrofoils, high-speed crafts, marine propellers, marine structures etc. Consequently, this book can be appropriate guidance for researchers and engineers in the context of marine engineering for recognition of the effects of ANNs in the prediction of different marine engineering problems.

Hashem Nowruzi received Ph.D in Marine eng. from Amirkabir University of Technology (Tehran Polytechnic) in 2019. His research interests include CFD, ANNs and marine energy. Mahdi Yousefifard received Ph.D in Marine eng. from AUT (Tehran Polytechnic) in 2014. He is currently an assistant professor at Babol Noshirvani University of Technology.