Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Conditions (eBook)

Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F. Almeida, Maria L. Simões, Sofia Manuel (Autoren)

eBook Download: PDF

2015 | 1st ed. 2016
X, 48 Seiten
Springer International Publishing (Verlag)
978-3-319-22294-3 (ISBN)

Infos

The main benefit of the book is that it explores available methodologies for both conducting in-situ measurements and adequately exploring the results, based on a case study that illustrates the benefits and difficulties of concurrent methodologies.

The case study corresponds to a set of 25 social housing dwellings where an extensive in situ measurement campaign was conducted. The dwellings are located in the same quarter of a city. Measurements included indoor temperature and relative humidity, with continuous log in different rooms of each dwelling, blower-door tests and complete outdoor conditions provided by a nearby weather station.

The book includes a variety of scientific and engineering disciplines, such as building physics, probability and statistics and civil engineering. It presents a synthesis of the current state of knowledge for benefit of professional engineers and scientists.

Inhalt

Preface 6
Acknowledgments 8
Contents 9
1 Introduction 11
Abstract 11
1.1 Motivation 11
1.2 Methodology 12
References 13
2 Indoor Hygrothermal Conditions 14
Abstract 14
2.1 Involved Parameters 14
2.1.1 Air Temperature 15
2.1.2 Relative Humidity 15
2.2 Standardized Methodologies 16
2.3 Literature Review 19
2.3.1 Building Performance Versus User Behaviour 19
2.3.2 Building Performance Indicators 19
References 20
3 Data Mining Techniques 22
Abstract 22
3.1 Principles 22
3.2 Basic Statistical Tools 22
3.2.1 Descriptive Statistics 23
3.2.2 Probability Distributions 23
3.2.2.1 Discrete Probability Distributions 24
3.2.2.2 Continuous Probability Distributions 24
3.2.3 Correlation Matrices 25
3.2.4 Multi-Way Frequency Tables 26
3.3 Multivariate Data Techniques 27
3.3.1 Principal Components and Factor Analysis 27
3.3.1.1 Principal Components 28
3.3.1.2 Factor Analysis 33
3.3.2 Discriminant and Cluster Analysis 34
3.3.2.1 Discriminant Analysis 34
3.3.2.2 Cluster Analysis 34
3.3.3 Multiple Regression Analysis 38
3.3.4 Classification Trees 39
References 39
4 Case Study 40
Abstract 40
4.1 Sample Description 40
4.2 In-Situ Campaign 40
4.3 Measurement Results 41
4.3.1 Outdoor Conditions 42
4.3.2 Indoor Temperature 43
4.3.3 Indoor Relative Humidity 44
References 45
5 Application of Data Mining Techniques 46
Abstract 46
5.1 Statistical Analysis of Data 46
5.2 Multivariate Data Analysis 49
6 Conclusions 55
Abstract 55

Produkt-Details

• Erscheint lt. Verlag: 24.8.2015
• Reihe/Serie: SpringerBriefs in Applied Sciences and Technology
• Reihe/Serie: SpringerBriefs in Applied Sciences and Technology
• Zusatzinfo: X, 48 p. 21 illus., 2 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Technik ► Maschinenbau
• Schlagworte: Air permeability • Data mining Statistical tools • Hygrothermal comfort • Indoor environment • multivariate analysis • Outdoor conditions
• ISBN-10: 3-319-22294-5 / 3319222945
• ISBN-13: 978-3-319-22294-3 / 9783319222943