Underwater Vehicle Control and Communication Systems Based on Machine Learning Techniques

The development of intelligent transportation systems, especially autonomous underwater vehicles, has become significant in marine engineering, with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization of autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including the study of experimental investigation combined with hydrodynamic characteristics backed by MATLAB® codes and simulation study results. Features: - Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. - Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. - Evaluates performance of particle swarm intelligence-based optimization techniques. - Reviews propulsion performance of the remote-controlled vehicles based on machine learning techniques. - Includes MATLAB® examples and simulation study results. This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.

Tien Anh Tran (IEEE Member, IMarEST Member) a Research Fellow at Seoul National University, Seoul city, South Korea. He is an Assistant Professor (Lecturer) at Department of Marine Engineering, Vietnam Maritime University, Haiphong City, Vietnam. Additionally, he is also an Honorary Professor at School of Computing Science and Engineering, Galgotias University, India. Kolla Bhanu Prakash is working as Professor and Research Group Head for A.I & Data Science Research group at KLEF. Subrata Chowdhury is perusing M.Tech at the Sreenivasa Institute of Technology and Management Studies, Chittoor Andhra Pradesh, India. Ivan Tam is an Associate Professor at Newcastle University in the UK with a wealth of experience in multi-disciplinary research and a strong track record of leading innovative projects. His research interest is in the clean fuel combustion process, exhaust emission control, energy management and renewable energy technology.

1. A Survey on Enhancement and Restoration of Underwater Image: Challenges, Techniques and Datasets. 2. Advances of Unmanned Autonomous Vehicle and Its Communication Systems. 3. Control Algorithms for Multiple Autonomous Underwater Vehicles to Cooperatively Encirle Intelligent Intrusion Devices. 4. Safety Management Based on Machine Learning for Identifying Unexpected Faults in Autonomous Underwater Vehicles. 5. Internet of Things and Machine Learning for Transportation System Using Adaptive Enhanced K-Nearest Neighbor Algorithm. 6. Optimization of Routing Protocols in ITS Using Elephant Heard Algorithm for Underwater Wireless Sensor Networks. 7. Effect of the Intelligent Transportation System into the Sustainable Environment and Ecology System. 8. An Application Oriented Integrated Unequal Clustering Algorithm for Wireless Senor Network.