Role of Rainfall and Catchment Characteristics on Urban Stormwater Quality by An Liu; Ashantha Goonetilleke; Prasanna EgodawattaThe key highlights of the book include an innovative rainfall classification methodology based on stormwater quality to support the planning and design of stormwater treatment systems. Additionally, this book provides a practical approach to effective stormwater treatment design and development of a methodology for rainfall selection to optimize stormwater treatment based on both its quality and quantity. The case study presented in this book evaluates how pollutant buildup on urban surfaces and stormwater runoff quality varies with a range of catchment characteristics based on different rainfall types. The information presented will be of particular interest to practitioners such as stormwater-treatment designers, urban planners and hydrologic and stormwater-quality model developers since the outcomes presented provide practical approaches to and recommendations for urban stormwater-quality improvement. Readers will benefit from a state-of-the-art critical review of literature on urban stormwater quality, an in-depth discussion on stormwater-quality processes providing guidance for engineering practice such as stormwater treatment design and model development, a comprehensive overview on the application of multivariate data analysis techniques and a paradigm of the integrated use of commercial models and mathematical equations to undertake a comprehensive, urban stormwater-quality investigation.
Efficient Learning Machines by Rahul Khanna; Mariette AwadMachine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna's synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.
Engineering Surveying by W. Schofield; Mark BreachEngineering Surveying 6th edition covers all the basic principles and practice of this complex subject and the authors bring expertise and clarity. This classic text should give readers a clear understanding of fundamentals such as vertical control, distance, angles and position right through to the most modern technologies.
ISBN: 9780080477626
Publication Date: 2007
Fundamentals of Civil Engineering by Richard H. McCuen; Edna Z. Ezzell; Melanie K. WongThis book presents educational material on 14 of the 24 outcomes identified in the ASCE Body of Knowledge as being important to success. Topics covered include: the humanities, social sciences, experimentation, sustainability, contemporary issues and historical perspectives, risk and uncertainty, communication, public policy, globalization, leadership, teamwork, attitudes, lifelong learning, and professional and ethical responsibilities.