This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.

Automation and Robotics in the Architecture, Engineering, and Construction Industry provides distinct and unified insight into current and future construction robotics, offering readers a comprehensive perspective for constructing a road map and illuminating improvements for a successful transition towards construction robotization. The book covers the fundamentals and applications of robotics, autonomous vehicles, and human-perceptive machines at construction sites. Through theoretical and experimental analyses, it examines the potential of robotics and automated systems for current and future fieldwork operations and identifies the factors that determine their implementation pace, adoption scale, and ubiquity throughout the industry. The book evaluates the technical, societal, and economic aspects of adopting robots in construction, both as standalone and collaborative systems, which in return can afford the opportunity to investigate these AI-enabled machines more systematically.

Automation and Robotics in the Architecture, Engineering, and Construction Industry provides distinct and unified insight into current and future construction robotics, offering readers a comprehensive perspective for constructing a road map and illuminating improvements for a successful transition towards construction robotization. The book covers the fundamentals and applications of robotics, autonomous vehicles, and human-perceptive machines at construction sites. Through theoretical and experimental analyses, it examines the potential of robotics and automated systems for current and future fieldwork operations and identifies the factors that determine their implementation pace, adoption scale, and ubiquity throughout the industry. The book evaluates the technical, societal, and economic aspects of adopting robots in construction, both as standalone and collaborative systems, which in return can afford the opportunity to investigate these AI-enabled machines more systematically.

This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.