(Ebook) Intelligent Data Mining and Analysis in Power and Energy Systems : Models and Applications for Smarter Efficient Power Systems by Zita A. Vale, Tiago Pinto, Michael Negnevitsky, Ganesh Kumar Venayagamoorthy ISBN 9781119834021, 9781119834052, 9781119834038, 1119834023, 1119834058, 1119834031

(Ebook) Intelligent Data Mining and Analysis in Power and Energy Systems : Models and Applications for Smarter Efficient Power Systems by Zita A. Vale, Tiago Pinto, Michael Negnevitsky, Ganesh Kumar Venayagamoorthy ISBN 9781119834021, 9781119834052, 9781119834038, 1119834023, 1119834058, 1119834031

Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.