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Data Mining and Machine Learning in Building Energy Analysis

Data Mining and Machine Learning in Building Energy Analysis PDF Author: Frédéric Magoules
Publisher: John Wiley & Sons
ISBN: 1118577485
Category : Computers
Languages : en
Pages : 187

Book Description
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 PDF Author: Frédéric Magoules
Publisher: John Wiley & Sons
ISBN: 1118577485
Category : Computers
Languages : en
Pages : 187

Book Description
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 PDF Author: Frédéric Magoules
Publisher: John Wiley & Sons
ISBN: 1118577590
Category : Computers
Languages : en
Pages : 186

Book Description
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.

Transition to Sustainable Buildings

Transition to Sustainable Buildings PDF Author: Organisation for Economic Co-operation and Development
Publisher: Organization for Economic Co-Operation & Developme
ISBN:
Category : Architecture
Languages : en
Pages : 292

Book Description
Buildings are the largest energy consuming sector in the world, and account for over one-third of total final energy consumption and an equally important source of carbon dioxide (CO2) emissions. Achieving significant energy and emissions reduction in the buildings sector is a challenging but achievable policy goal. Transition to Sustainable Buildings presents detailed scenarios and strategies to 2050, and demonstrates how to reach deep energy and emissions reduction through a combination of best available technologies and intelligent public policy. This IEA study is an indispensible guide for decision makers, providing informative insights on: cost-effective options, key technologies and opportunities in the buildings sector; solutions for reducing electricity demand growth and flattening peak demand; effective energy efficiency policies and lessons learned from different countries; future trends and priorities for ASEAN, Brazil, China, the European Union, India, Mexico, Russia, South Africa and the United States; implementing a systems approach using innovative products in a cost effective manner; and pursuing whole-building (e.g. zero energy buildings) and advanced-component policies to initiate a fundamental shift in the way energy is consumed.

Inverse Heat Conduction

Inverse Heat Conduction PDF Author: James V. Beck
Publisher: James Beck
ISBN: 9780471083191
Category : Mathematics
Languages : en
Pages : 336

Book Description
Here is the only commercially published work to deal with the engineering problem of determining surface heat flux and temperature history based on interior temperature measurements. Provides the analytical techniques needed to arrive at otherwise difficult solutions, summarizing the findings of the last ten years. Topics include the steady state solution, Duhamel's Theorem, ill-posed problems, single future time step, and more.

Principles of Data Mining

Principles of Data Mining PDF Author: David J. Hand
Publisher: MIT Press
ISBN: 9780262082907
Category : Computers
Languages : en
Pages : 594

Book Description
The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Data-Driven Modelling of Non-Domestic Buildings Energy Performance

Data-Driven Modelling of Non-Domestic Buildings Energy Performance PDF Author: Saleh Seyedzadeh
Publisher: Springer Nature
ISBN: 303064751X
Category : Architecture
Languages : en
Pages : 161

Book Description
This book outlines the data-driven modelling of building energy performance to support retrofit decision-making. It explains how to determine the appropriate machine learning (ML) model, explores the selection and expansion of a reasonable dataset and discusses the extraction of relevant features and maximisation of model accuracy. This book develops a framework for the quick selection of a ML model based on the data and application. It also proposes a method for optimising ML models for forecasting buildings energy loads by employing multi-objective optimisation with evolutionary algorithms. The book then develops an energy performance prediction model for non-domestic buildings using ML techniques, as well as utilising a case study to lay out the process of model development. Finally, the book outlines a framework to choose suitable artificial intelligence methods for modelling building energy performances. This book is of use to both academics and practising energy engineers, as it provides theoretical and practical advice relating to data-driven modelling for energy retrofitting of non-domestic buildings.

Fundamentals of Machine Learning for Predictive Data Analytics, second edition

Fundamentals of Machine Learning for Predictive Data Analytics, second edition PDF Author: John D. Kelleher
Publisher: MIT Press
ISBN: 0262361108
Category : Computers
Languages : en
Pages : 853

Book Description
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Digital Cities Roadmap

Digital Cities Roadmap PDF Author: Arun Solanki
Publisher: John Wiley & Sons
ISBN: 1119792053
Category : Computers
Languages : en
Pages : 546

Book Description
DIGITAL CITIES ROADMAP This book details applications of technology to efficient digital city infrastructure and its planning, including smart buildings. Rapid urbanization, demographic changes, environmental changes, and new technologies are changing the views of urban leaders on sustainability, as well as creating and providing public services to tackle these new dynamics. Sustainable development is an objective by which the processes of planning, implementing projects, and development is aimed at meeting the needs of modern communities without compromising the potential of future generations. The advent of Smart Cities is the answer to these problems. Digital Cities Roadmap provides an in-depth analysis of design technologies that lay a solid foundation for sustainable buildings. The book also highlights smart automation technologies that help save energy, as well as various performance indicators needed to make construction easier. The book aims to create a strong research community, to have a deep understanding and the latest knowledge in the field of energy and comfort, to offer solid ideas in the nearby future for sustainable and resilient buildings. These buildings will help the city grow as a smart city. The smart city has also a focus on low energy consumption, renewable energy, and a small carbon footprint. Audience The information provided in this book will be of value to researchers, academicians and industry professionals interested in IoT-based architecture and sustainable buildings, energy efficiency and various tools and methods used to develop green technologies for construction in smart cities.

Building Energy Audits-Diagnosis and Retrofitting

Building Energy Audits-Diagnosis and Retrofitting PDF Author: Constantinos A. Balaras
Publisher: MDPI
ISBN: 3039438298
Category : Science
Languages : en
Pages : 298

Book Description
The book “Building Energy Audits-Diagnosis and Retrofitting” is a collection of twelve papers that focus on the built environment in order to systematically collect and analyze relevant data for the energy use profile of buildings and extended for the sustainability assessment of the built environment. The contributions address historic buildings, baselines for non-residential buildings from energy performance audits, and from in-situ measurements, monitoring, and analysis of data, and verification of energy saving and model calibration for various building types. The works report on how to diagnose existing problems and identify priorities, assess, and quantify the opportunities and measures that improve the overall building performance and the environmental quality and well-being of occupants in non-residential buildings and houses. Several case studies and lessons learned from the field are presented to help the readers identify, quantify, and prioritize effective energy conservation and efficiency measures. Finally, a new urban sustainability audit and rating method of the built environment addresses the complexities of the various issues involved, providing practical tools that can be adapted to match local priorities in order to diagnose and evaluate the current state and future scenarios towards meeting specific sustainable development goals and local priorities.

Innovation in Information Systems and Technologies to Support Learning Research

Innovation in Information Systems and Technologies to Support Learning Research PDF Author: Mohammed Serrhini
Publisher: Springer Nature
ISBN: 3030367789
Category : Technology & Engineering
Languages : en
Pages : 659

Book Description
This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.