Validation of neural network model for predicting airtightness of residential and non-residential units in Poland
•Validation of neural network model for predicting airtightness of residential and non-residential units developed in Croatia.•Formation of new validation data set of residential and non-residential units obtained in Poland.•Results obtained by measurement and prediction model indicates that the mod...
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| Veröffentlicht in: | Energy and buildings 2016-12, Vol.133, p.423-432 |
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| creator | Krstić, Hrvoje Otković, Irena Ištoka Kosiński, Piotr Wójcik, Robert |
| description | •Validation of neural network model for predicting airtightness of residential and non-residential units developed in Croatia.•Formation of new validation data set of residential and non-residential units obtained in Poland.•Results obtained by measurement and prediction model indicates that the model gives consistent results on the new validation set.
This paper presents validation of the neural network model for predicting airtightness of residential and non-residential units. Proposed model developed in previous research utilizes a neural network in prediction of airtightness and it is obtained based on in situ measurements at 58 units in Croatia. Model applicability earlier was tested by independent validation through 20 additional measurements in Croatia and on 5 measurements in Serbia. This paper presents validation of neural network model for predicting airtightness of residential and non-residential units on database formed beyond the regional area. Database used for model validation in this paper consists of 20 residential and non-residential units from Poland with building construction technology similar to Croatian ones. Comparison of the results obtained by measurements and prediction model indicates that the model gives consistent results on the validation data set with similar building construction technology and demonstrates that model is not locally conditioned. |
| doi_str_mv | 10.1016/j.enbuild.2016.10.011 |
| format | Article |
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This paper presents validation of the neural network model for predicting airtightness of residential and non-residential units. Proposed model developed in previous research utilizes a neural network in prediction of airtightness and it is obtained based on in situ measurements at 58 units in Croatia. Model applicability earlier was tested by independent validation through 20 additional measurements in Croatia and on 5 measurements in Serbia. This paper presents validation of neural network model for predicting airtightness of residential and non-residential units on database formed beyond the regional area. Database used for model validation in this paper consists of 20 residential and non-residential units from Poland with building construction technology similar to Croatian ones. Comparison of the results obtained by measurements and prediction model indicates that the model gives consistent results on the validation data set with similar building construction technology and demonstrates that model is not locally conditioned.</description><identifier>ISSN: 0378-7788</identifier><identifier>EISSN: 1872-6178</identifier><identifier>DOI: 10.1016/j.enbuild.2016.10.011</identifier><language>eng</language><publisher>Lausanne: Elsevier B.V</publisher><subject>Air flow ; Air tightness ; Airtightness ; Build quality ; Building construction ; Building construction technology ; Building envelope ; Conditioning ; Construction ; Data bases ; Mathematical models ; Modelling ; Neural networks ; Prediction models ; Residential areas ; Residential buildings ; Studies ; Technology</subject><ispartof>Energy and buildings, 2016-12, Vol.133, p.423-432</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Elsevier BV Dec 1, 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c337t-791e66082370c93a57656c12bf1ef088b41193ba5db4d20cdf16815a383e5343</citedby><cites>FETCH-LOGICAL-c337t-791e66082370c93a57656c12bf1ef088b41193ba5db4d20cdf16815a383e5343</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.enbuild.2016.10.011$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Krstić, Hrvoje</creatorcontrib><creatorcontrib>Otković, Irena Ištoka</creatorcontrib><creatorcontrib>Kosiński, Piotr</creatorcontrib><creatorcontrib>Wójcik, Robert</creatorcontrib><title>Validation of neural network model for predicting airtightness of residential and non-residential units in Poland</title><title>Energy and buildings</title><description>•Validation of neural network model for predicting airtightness of residential and non-residential units developed in Croatia.•Formation of new validation data set of residential and non-residential units obtained in Poland.•Results obtained by measurement and prediction model indicates that the model gives consistent results on the new validation set.
This paper presents validation of the neural network model for predicting airtightness of residential and non-residential units. Proposed model developed in previous research utilizes a neural network in prediction of airtightness and it is obtained based on in situ measurements at 58 units in Croatia. Model applicability earlier was tested by independent validation through 20 additional measurements in Croatia and on 5 measurements in Serbia. This paper presents validation of neural network model for predicting airtightness of residential and non-residential units on database formed beyond the regional area. Database used for model validation in this paper consists of 20 residential and non-residential units from Poland with building construction technology similar to Croatian ones. Comparison of the results obtained by measurements and prediction model indicates that the model gives consistent results on the validation data set with similar building construction technology and demonstrates that model is not locally conditioned.</description><subject>Air flow</subject><subject>Air tightness</subject><subject>Airtightness</subject><subject>Build quality</subject><subject>Building construction</subject><subject>Building construction technology</subject><subject>Building envelope</subject><subject>Conditioning</subject><subject>Construction</subject><subject>Data bases</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Neural networks</subject><subject>Prediction models</subject><subject>Residential areas</subject><subject>Residential buildings</subject><subject>Studies</subject><subject>Technology</subject><issn>0378-7788</issn><issn>1872-6178</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LAzEQhoMoWD9-ghDwvDWzaTbpSUT8AkEP4jVkk1lNXZOaZBX_vSn14M3TMO_MMyEPISfA5sCgO1vNMfSTH928rW3N5gxgh8xAybbpQKpdMmNcqkZKpfbJQc4rxlgnJMzIx7MZvTPFx0DjQANOyYy1lK-Y3uh7dDjSISa6Tui8LT68UONT8S-vJWDOGyZh9g5D8RU0wdEQQ_M3m4IvmfpAH-NY50dkbzBjxuPfekierq-eLm-b-4ebu8uL-8ZyLksjl4Bdx1TLJbNLboTsRGeh7QfAgSnVLwCWvDfC9QvXMusG6BQIwxVHwRf8kJxuz65T_JgwF72KUwr1RV25FpRgXNQtsd2yKeaccNDr5N9N-tbA9EauXulfuXojdxNXuZU733JYf_DpMelsPQZbJSW0Rbvo_7nwA7H3hqM</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Krstić, Hrvoje</creator><creator>Otković, Irena Ištoka</creator><creator>Kosiński, Piotr</creator><creator>Wójcik, Robert</creator><general>Elsevier B.V</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>SOI</scope></search><sort><creationdate>20161201</creationdate><title>Validation of neural network model for predicting airtightness of residential and non-residential units in Poland</title><author>Krstić, Hrvoje ; Otković, Irena Ištoka ; Kosiński, Piotr ; Wójcik, Robert</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c337t-791e66082370c93a57656c12bf1ef088b41193ba5db4d20cdf16815a383e5343</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Air flow</topic><topic>Air tightness</topic><topic>Airtightness</topic><topic>Build quality</topic><topic>Building construction</topic><topic>Building construction technology</topic><topic>Building envelope</topic><topic>Conditioning</topic><topic>Construction</topic><topic>Data bases</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>Neural networks</topic><topic>Prediction models</topic><topic>Residential areas</topic><topic>Residential buildings</topic><topic>Studies</topic><topic>Technology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Krstić, Hrvoje</creatorcontrib><creatorcontrib>Otković, Irena Ištoka</creatorcontrib><creatorcontrib>Kosiński, Piotr</creatorcontrib><creatorcontrib>Wójcik, Robert</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Energy and buildings</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Krstić, Hrvoje</au><au>Otković, Irena Ištoka</au><au>Kosiński, Piotr</au><au>Wójcik, Robert</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validation of neural network model for predicting airtightness of residential and non-residential units in Poland</atitle><jtitle>Energy and buildings</jtitle><date>2016-12-01</date><risdate>2016</risdate><volume>133</volume><spage>423</spage><epage>432</epage><pages>423-432</pages><issn>0378-7788</issn><eissn>1872-6178</eissn><abstract>•Validation of neural network model for predicting airtightness of residential and non-residential units developed in Croatia.•Formation of new validation data set of residential and non-residential units obtained in Poland.•Results obtained by measurement and prediction model indicates that the model gives consistent results on the new validation set.
This paper presents validation of the neural network model for predicting airtightness of residential and non-residential units. Proposed model developed in previous research utilizes a neural network in prediction of airtightness and it is obtained based on in situ measurements at 58 units in Croatia. Model applicability earlier was tested by independent validation through 20 additional measurements in Croatia and on 5 measurements in Serbia. This paper presents validation of neural network model for predicting airtightness of residential and non-residential units on database formed beyond the regional area. Database used for model validation in this paper consists of 20 residential and non-residential units from Poland with building construction technology similar to Croatian ones. Comparison of the results obtained by measurements and prediction model indicates that the model gives consistent results on the validation data set with similar building construction technology and demonstrates that model is not locally conditioned.</abstract><cop>Lausanne</cop><pub>Elsevier B.V</pub><doi>10.1016/j.enbuild.2016.10.011</doi><tpages>10</tpages></addata></record> |
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| issn | 0378-7788 1872-6178 |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Air flow Air tightness Airtightness Build quality Building construction Building construction technology Building envelope Conditioning Construction Data bases Mathematical models Modelling Neural networks Prediction models Residential areas Residential buildings Studies Technology |
| title | Validation of neural network model for predicting airtightness of residential and non-residential units in Poland |
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