The mold infestation of buildings classified by Kohonen Self-Organizing Maps with boundaries determined by Ward clustering using multidimensional data from gas sensors
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F24%3A00382493" target="_blank" >RIV/68407700:21110/24:00382493 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1088/1742-6596/2911/1/012019" target="_blank" >http://dx.doi.org/10.1088/1742-6596/2911/1/012019</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1088/1742-6596/2911/1/012019" target="_blank" >10.1088/1742-6596/2911/1/012019</a>
Alternative languages
Result language
angličtina
Original language name
The mold infestation of buildings classified by Kohonen Self-Organizing Maps with boundaries determined by Ward clustering using multidimensional data from gas sensors
Original language description
Mold infestation of buildings occurs when the moisture content of partitions increases, and is a significant problem in building operation. This problem is substantial in terms of architecture and building construction, residents' health and aesthetic reasons. There are numerous methods of evaluating mold infestation, among them important ones include traditional biological, molecular microbiological, and chemical techniques. One of the newer methods is application of gas sensors arrays, which form an electronic nose when combined with a properly chosen data analysis algorithm. The critical issue connected with correct functioning of an electronic nose is selection of the appropriate mathematical model enabling interpretation and visualization of the results – multidimensional signals originating from sensors array. In this work a Kohonen Self-Organizing-Map with hexagonal topology was used for presenting the similarity between measurements of buildings that are in different stages of mold infestation, as well as reference sample of clean air and decayed timber. On the two-dimensional visualization of Kohonen map, the boundaries created by applying the hierarchical Ward clustering method were superimposed. This procedure allowed showing which observation would be assigned to which clusters connected with level of mold infestation.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20705 - Remote sensing
Result continuities
Project
<a href="/en/project/GA22-00420S" target="_blank" >GA22-00420S: Functional characteristics and environmental impact of lime plasters with natural additives for historical building renovation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Journal of Physics: Conference Series 2911
ISBN
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ISSN
1742-6588
e-ISSN
1742-6596
Number of pages
6
Pages from-to
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Publisher name
IOP Publishing Ltd.
Place of publication
Bristol
Event location
Miskolctapolca
Event date
Sep 4, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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