Machine Learning and Data Analysis for Energy Efficiency in Buildings - Zhao, Tianyi; Zhang, Chengyu; Jiang, Ben
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Machine Learning and Data Analysis for Energy Efficiency in Buildings: Intelligent Operation, Maintenance, and Optimization of Building Energy Systems is a guidebook for big data use in energy efficiency and control. This book begins with an introduction to data basics, from selecting and evaluating data to the identification and repair of abnormalities. In Part II, data mining is covered and applied to energy forecasting, including long- and short-term predictions, and the introduction of occupant-focused behaviour analysis. Part III breaks down the current methods for supply and demand…mehr

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Produktbeschreibung
Machine Learning and Data Analysis for Energy Efficiency in Buildings: Intelligent Operation, Maintenance, and Optimization of Building Energy Systems is a guidebook for big data use in energy efficiency and control. This book begins with an introduction to data basics, from selecting and evaluating data to the identification and repair of abnormalities. In Part II, data mining is covered and applied to energy forecasting, including long- and short-term predictions, and the introduction of occupant-focused behaviour analysis. Part III breaks down the current methods for supply and demand applications, including a variety of solutions for monitoring and managing energy use and supply. Case studies are included in each part to assisting in evaluation and implementation of these techniques across building energy systems. Working from the fundamentals of big data analysis to a complete method for building energy assessment, flexibility, and management, ‘Machine Learning and Data Analysis for Energy Efficiency in Buildings’ will provide students, researchers, and professionals with an essential cutting-edge resource in this important technology.
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Autorenporträt
Zhao Tianyi is the Deputy Dean and an Associate Professor of the School of Civil Engineering at Dalian University of Technology. He is the Group Lead of the On-line Automation Solutions Institute for Sustainability in Energy and Buildings (OASIS-EB). This group focuses on investigating intelligent regulation and control methods for building energy systems, incorporating advanced technologies such as the Internet of Things, big data, and artificial intelligence. He has published over 100 peer-reviewed articles in journals.