Anass Cherrafi – författare

This book explores and highlights the latest techniques and applications of artificial intelligence (AI) and fuzzy logic in the development of intelligent transportation systems (ITS). It offers a detailed examination of how to leverage these technologies to solve complex transportation challenges, such as traffic congestion, route optimization, and autonomous vehicle navigation. Artificial Intelligence and Fuzzy Logic for Next Generation Intelligent Transportation employs several novel approaches and special design features. It includes case studies and real-world examples illustrating the practical applications of the technologies under review. Furthermore, it integrates interdisciplinary perspectives, combining insights from computer science, engineering, urban planning, and environmental science. Each chapter is self-contained, providing both theoretical background and practical insights, making it accessible to a broad audience. Additionally, this book features contributions from leading experts in the field, ensuring that the content is both current and relevant.Presents advanced methodologies in AI and fuzzy logic, specifically designed to enhance ITSsOffers a detailed examination of how technologies can be leveraged to solve complex transportation challenges, such as traffic congestion, route optimization, and autonomous vehicle navigationBridges the gap between theoretical research and practical implementation, demonstrating how emerging technologies can be applied to real-world problemsIncludes theoretical foundations, algorithmic developments, and practical case studies specifically related to AI in the context of smart transportationDiscusses topics such as predictive weather impact on traffic management, enhancing road safety with AI and fuzzy logic, and smart parking systems in urban areasIt is written for researchers, engineers, and practitioners in the field, as well as policymakers and academic scholars interested in the future of transportation.

They address various aspects of artificial intelligence such as smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications.

This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco.   The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.