Condition Monitoring Using Computational Intelligence Methods

Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. It examines both the commonly used traffic analysis methodologies as well the emerging ones that use deep learning methods. The book also shows how to understand statistical models and machine learning algorithms, and how to apply them to traffic modelling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning is for researchers and practitioners who want to improve the performance of intelligent transportation systems.

SAR Oceanography: Monitoring Oceanic Dynamics with Synthetic Aperture Radar is an authoritative reference for scientists and professionals involved in marine remote sensing and oceanography. The book addresses the critical need for advanced techniques to observe and analyze ocean surface phenomena such as wind, waves, currents, internal waves, and oil spills using SAR technology. It emphasizes the importance of SAR in tropical cyclone monitoring, providing insights into high-resolution, all-weather, day-and-night observations essential for climate research, disaster response, and maritime safety. The content is divided into chapters covering SAR algorithms, applications in different oceanic processes, and recent technological developments. It offers practical case studies and validation methods, making it a valuable resource for researchers, meteorologists, environmental policymakers, and remote sensing specialists. This publication enhances understanding of ocean dynamics and supports