书目名称 | Data-driven Analytics for Sustainable Buildings and Cities | 副标题 | From Theory to Appli | 编辑 | Xingxing Zhang | 视频video | | 概述 | Explores the multidisciplinary fields of energy systems, occupant behavior, thermal comfort, and air quality.Applies a wide range of methods from classical statistics, machine learning, and artificial | 丛书名称 | Sustainable Development Goals Series | 图书封面 |  | 描述 | This book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.. . | 出版日期 | Book 2021 | 关键词 | Energy; Thermal Comfort; Occupant Behavior; District Control; Future Climate; Neural Networks; Genetic Alg | 版次 | 1 | doi | https://doi.org/10.1007/978-981-16-2778-1 | isbn_softcover | 978-981-16-2780-4 | isbn_ebook | 978-981-16-2778-1Series ISSN 2523-3084 Series E-ISSN 2523-3092 | issn_series | 2523-3084 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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