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Data Mining And Machine Learning In Building Energy Analysis


Data Mining And Machine Learning In Building Energy Analysis
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Data Mining And Machine Learning In Building Energy Analysis


Data Mining And Machine Learning In Building Energy Analysis
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Author : Frédéric Magoules
language : en
Publisher: John Wiley & Sons
Release Date : 2016-01-05

Data Mining And Machine Learning In Building Energy Analysis written by Frédéric Magoules and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-05 with Computers categories.


The energy consumption of a building has, in recent years, become a determining factor during its design and construction. With carbon footprints being a growing issue, it is important that buildings be optimized for energy conservation and CO2 reduction. This book therefore presents AI models and optimization techniques related to this application. The authors start with a review of recent models for the prediction of building energy consumption: engineering methods, statistical methods, artificial intelligence methods, ANNs and SVMs in particular. The book then focuses on SVMs, by first applying them to building energy consumption, then presenting the principles and various extensions, and SVR. The authors then move on to RDP, which they use to determine building energy faults through simulation experiments before presenting SVR model reduction methods and the benefits of parallel computing. The book then closes by presenting some of the current research and advancements in the field.



Data Mining And Machine Learning In Building Energy Analysis


Data Mining And Machine Learning In Building Energy Analysis
DOWNLOAD
Author : Frédéric Magoules
language : en
Publisher: John Wiley & Sons
Release Date : 2016-01-05

Data Mining And Machine Learning In Building Energy Analysis written by Frédéric Magoules and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-05 with Computers categories.


The energy consumption of a building has, in recent years, become a determining factor during its design and construction. With carbon footprints being a growing issue, it is important that buildings be optimized for energy conservation and CO2 reduction. This book therefore presents AI models and optimization techniques related to this application. The authors start with a review of recent models for the prediction of building energy consumption: engineering methods, statistical methods, artificial intelligence methods, ANNs and SVMs in particular. The book then focuses on SVMs, by first applying them to building energy consumption, then presenting the principles and various extensions, and SVR. The authors then move on to RDP, which they use to determine building energy faults through simulation experiments before presenting SVR model reduction methods and the benefits of parallel computing. The book then closes by presenting some of the current research and advancements in the field.



Intelligent Data Mining And Analysis In Power And Energy Systems


Intelligent Data Mining And Analysis In Power And Energy Systems
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Author : Zita A. Vale
language : en
Publisher: John Wiley & Sons
Release Date : 2022-12-13

Intelligent Data Mining And Analysis In Power And Energy Systems written by Zita A. Vale and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-13 with Technology & Engineering categories.


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.



Data Driven Analytics For Sustainable Buildings And Cities


Data Driven Analytics For Sustainable Buildings And Cities
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Author : Xingxing Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-09-11

Data Driven Analytics For Sustainable Buildings And Cities written by Xingxing Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-11 with Social Science categories.


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.



Big Data Analytics Methods


Big Data Analytics Methods
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Author : Peter Ghavami
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2019-12-16

Big Data Analytics Methods written by Peter Ghavami and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Business & Economics categories.


Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.



Applied Data Analysis And Modeling For Energy Engineers And Scientists


Applied Data Analysis And Modeling For Energy Engineers And Scientists
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Author : T. Agami Reddy
language : en
Publisher: Springer Nature
Release Date : 2023-10-18

Applied Data Analysis And Modeling For Energy Engineers And Scientists written by T. Agami Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-18 with Business & Economics categories.


Now in a thoroughly revised and expanded second edition, this classroom-tested text demonstrates and illustrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability, statistics, experimental design, regression, optimization, parameter estimation, inverse modeling, risk analysis, decision-making, and sustainability assessment methods to energy processes and systems. It provides a formal structure that offers a broad and integrative perspective to enhance knowledge, skills, and confidence to work in applied data analysis and modeling problems. This new edition also reflects recent trends and advances in statistical modeling as applied to energy and building processes and systems. It includes numerous examples from recently published technical papers to nurture and stimulate a more research-focused mindset. How the traditional stochastic data modeling approaches are complemented by data analytic algorithmic models such as machine learning and data mining are also discussed. The important societal issues related to the sustainability of energy systems are presented, and a formal structure is proposed meant to classify the various assessment methods found in the literature. Applied Data Analysis and Modeling for Energy Engineers and Scientists is designed for senior-level undergraduate and graduate instruction in energy engineering and mathematical modeling, for continuing education professional courses, and as a self-study reference book for working professionals. In order for readers to have exposure and proficiency with performing hands-on analysis, the open-source Python and R programming languages have been adopted in the form of Jupyter notebooks and R markdown files, and numerous data sets and sample computer code reflective of real-world problems are available online.



Artificial Intelligence Techniques For A Scalable Energy Transition


Artificial Intelligence Techniques For A Scalable Energy Transition
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Nature
Release Date : 2020-06-19

Artificial Intelligence Techniques For A Scalable Energy Transition written by Moamar Sayed-Mouchaweh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-19 with Technology & Engineering categories.


This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).



Investigating The Human Behavior Side Of Building Energy Efficiency


Investigating The Human Behavior Side Of Building Energy Efficiency
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Author : Chao Chen
language : en
Publisher:
Release Date : 2013

Investigating The Human Behavior Side Of Building Energy Efficiency written by Chao Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.


We describe and evaluate each of these contributions using electricity consumption data from actual smart homes as part of the CASAS smart home project. In each case we illustrate the efficacy of these algorithms to gaining insights on human behavior and its impact on energy consumption, and offer ideas for using these insights to promote sustainable behaviors.



Big Data Application In Power Systems


Big Data Application In Power Systems
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Author : Reza Arghandeh
language : en
Publisher: Elsevier
Release Date : 2017-11-27

Big Data Application In Power Systems written by Reza Arghandeh and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-27 with Science categories.


Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories and pathways for utilizing big data value in smart grids. Provides expert analysis of the latest developments by global authorities Contains detailed references for further reading and extended research Provides additional cross-disciplinary lessons learned from broad disciplines such as statistics, computer science and bioinformatics Focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data



Mining Hidden Knowledge From Measured Data For Improving Building Energy Performance


Mining Hidden Knowledge From Measured Data For Improving Building Energy Performance
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Author : Zhun Yu
language : en
Publisher:
Release Date : 2012

Mining Hidden Knowledge From Measured Data For Improving Building Energy Performance written by Zhun Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.