Application of data mining techniques in the analysis of indoor hygrothermal conditions [electronic resource] / Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F. Almeida, Maria L. Simões, Sofia Manuel.
2015
TD883.17
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Title
Application of data mining techniques in the analysis of indoor hygrothermal conditions [electronic resource] / Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F. Almeida, Maria L. Simões, Sofia Manuel.
ISBN
9783319222943 (electronic book)
3319222945 (electronic book)
9783319222936
3319222937
3319222945 (electronic book)
9783319222936
3319222937
Published
Cham : Springer, [2015]
Copyright
©2016
Language
English
Description
1 online resource (x, 48 pages).
Item Number
10.1007/978-3-319-22294-3 doi
Call Number
TD883.17
Dewey Decimal Classification
628.53
Summary
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.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
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Series
SpringerBriefs in applied sciences and technology.
Available in Other Form
Print version: 9783319222936
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Table of Contents
Introduction
Indoor hygrothermal conditions
Data mining techniques
Case Study
Application of data mining techniques
Conclusions.
Indoor hygrothermal conditions
Data mining techniques
Case Study
Application of data mining techniques
Conclusions.