Support Vector Machine (SVM)-Based Optimal Design Procedure of Fly Ash Blended Concrete
Autor: | Xiao-Yong Wang, Yi Han, Jong Yeon Lim, Tae Wan Kim |
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Rok vydání: | 2021 |
Předmět: |
Optimal design
Computer science business.industry Mechanical Engineering 0211 other engineering and technologies 020101 civil engineering 02 engineering and technology Machine learning computer.software_genre 0201 civil engineering Support vector machine Mechanics of Materials Fly ash 021105 building & construction General Materials Science Artificial intelligence business computer |
Zdroj: | Key Engineering Materials. 894:103-108 |
ISSN: | 1662-9795 |
DOI: | 10.4028/www.scientific.net/kem.894.103 |
Popis: | A support vector machine (SVM) is widely used for predicting the properties of fly ash blended concrete. However, the studies about the optimal design of fly ash blended concrete based on SVM are very limit. This study shows an SVM-based optimal design procedure of fly ash blended concrete. First, we built an SVM model and evaluated the compressive strength of fly ash blended concrete considering the effects of water to binder ratio, fly ash replacement ratio, and test ages. Second, we made parameter studies based on the SVM model. The parameter studies show that fly ash can improve the late age strength of concrete. This improvement is obvious for concrete with lower water to binder ratio. The optimal fly ash replacement ratio increases as the water to binder ratio decreases. |
Databáze: | OpenAIRE |
Externí odkaz: |
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