Pattern Classification Using Ensemble 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.

Prestressing concrete technology is critical to understanding problems in existing civic structures including railway and highway bridges; to the rehabilitation of older structures; and to the design of new high-speed railway and long-span highway bridges. Analysis and Design of Prestressed Concrete delivers foundational concepts, and the latest research and design methods for the engineering of prestressed concrete, paying particular attention to crack resistance in the design of high-speed railway and long-span highway prestressed concrete bridges. The volume offers readers a comprehensive resource on prestressing technology and applications, as well as the advanced treatment of prestress losses and performance. Key aspects of this volume include analysis and design of prestressed concrete structures using a prestressing knowledge system, from initial stages to service; detailed loss calculation; time-dependent analysis on cross-sectional stresses; straightforward, simplified methods

Knowledge Engineering for Innovation and Sustainability is an interdisciplinary examination, not only of knowledge engineering, but also innovation, allowing environmental scientists to gain a better understanding of technological solutions and innovative methods. It is organized in a methodical way, first by defining sustainability and innovation, then by laying out a conceptual framework. The book goes on to explore causality and systems thinking for examining a particular phenomenon, and then presents processes for analysis and design. Finally, it lays out the narrative of sustainability as well as what needs to be done to ensure the future of sustainability. By applying key concepts of innovation and knowledge engineering to sustainability problems, Knowledge Engineering for Innovation and Sustainability provides a structured approach to putting theory into practice for sustainable development.

Nanomaterials possess special mechanical, electrical, and electronic properties. As a result, nanomaterials play a significant role in various nanoelectromechanical systems. Some of these materials include nanoparticles, nanowires, nanotubes, nanotube resonators, and nanoactuators. These structures are broadly utilized in civil, mechanical, and aerospace engineering. The dynamic analysis of nanostructures is important, because one must have knowledge about the mechanical behaviours to get an accurate prediction of dynamic characteristics. Conducting experiments at the nanoscale size is both complicated and expensive. Therefore, the development of appropriate mathematical models for the study of the dynamic behaviour of nanostructures is important. These models/problems are governed by linear/nonlinear differential equations which are not always possible to solve analytically. This deficiency compels us to search for numerical and computational methods. This book provides a detailed exp