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한국건축시공학회 / v.11, no.3, 2011년, pp.238-246 
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( Support Vector Machine Model to Select Exterior Materials ) |
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| 초 록 |
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| 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. |
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| 키워드 |
| exterior material;one-against-all;support vector machine; |
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한국건축시공학회지 / v.11, no.3, 2011년, pp.238-246
한국건축시공학회
ISSN : 1598-2033
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO201121539232523)
언어 : 영어 |
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| 논문 제공 : KISTI 한국과학기술정보연구원 |
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