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Predicting house damage class using artificial intelligence method

Osman-Schlegel, N. Y. 2013, Predicting house damage class using artificial intelligence method, in HKICEAS 2013 : Proceedings of the 2013 Engineering and Applied Science Hong Kong International Conference, [Conference], [Hong Kong, China], pp. 486-491.

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Title Predicting house damage class using artificial intelligence method
Author(s) Osman-Schlegel, N. Y.
Conference name Engineering and Applied Science. Hong Kong International Conference (2nd : 2013 : Hong Kong, China)
Conference location Hong Kong, China
Conference dates 19 - 21 Dec. 2013
Title of proceedings HKICEAS 2013 : Proceedings of the 2013 Engineering and Applied Science Hong Kong International Conference
Editor(s) [Unknown]
Publication date 2013
Conference series Engineering and Applied Science Hong Kong International Conference
Start page 486
End page 491
Total pages 6
Publisher [Conference]
Place of publication [Hong Kong, China]
Keyword(s) house damage
artificial intelligence
light structures
damage class
structural movements
Summary The unsatisfactory performance of light structures founded on expansive soils subject to seasonal movements is frequently reported since the early 1950's in Australia. Excessive movements have caused damage to numerous structures that have not been adequately designed to accommodate soil volume changes. However, the sole presence of expansive soil is not necessarily the main cause of damage. Other factors such as vegetation, climate factors, types of construction materials and geology type may also contribute. This paper presents a model which predicts the damage class by analyzing combinations of the contributing factors using artificial intelligence methods. This model can help to identify if any serious and urgent repairs are necessary and immediate actions could be initiated without delay.
ISBN 9789868741744
Language eng
Field of Research 129999 Built Environment and Design not elsewhere classified
Socio Economic Objective 970112 Expanding Knowledge in Built Environment and Design
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2013, The Authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30062600

Document type: Conference Paper
Collections: School of Architecture and Built Environment
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.