Overview
- Explores available methodologies for both conducting in-situ measurements and adequately explore the results
- Involves a variety of scientific and engineering disciplines, such as building physics, probability and statistics and civil engineering
- Offers a synthesis of the current state of knowledge for benefit of professional engineers and scientists
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
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Table of contents (6 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Conditions
Authors: Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F. Almeida, Maria L. Simões, Sofia Manuel
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-3-319-22294-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2016
Softcover ISBN: 978-3-319-22293-6Published: 03 September 2015
eBook ISBN: 978-3-319-22294-3Published: 24 August 2015
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: X, 48
Number of Illustrations: 19 b/w illustrations, 2 illustrations in colour
Topics: Building Repair and Maintenance, Structural Materials, Data Mining and Knowledge Discovery