Support Vector Machine Model to Select Exterior Materials

Title
Support Vector Machine Model to Select Exterior Materials
Author(s)
김상용
Keywords
exterior material; one-against-all; support vector machine
Issue Date
201106
Publisher
한국건축시공학회
Citation
한국건축시공학회지, v.11, no.3, pp.238 - 246
Abstract
Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.
URI
http://hdl.handle.net/YU.REPOSITORY/24978
ISSN
1598-2033
Appears in Collections:
건축학부 > 건축학부 > Articles
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