Journal
COMPUTERS AND CONCRETE
Volume 4, Issue 4, Pages 299-316Publisher
TECHNO-PRESS
DOI: 10.12989/cac.2007.4.4.299
Keywords
concrete strength; strength prediction; support vector regression (SVR); concrete mix proportion data; kernel function
Categories
Funding
- National Research Foundation of Korea [R01-2006-000-10610-0, 핵06A2102] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Ask authors/readers for more resources
The compressive strength of concrete is a commonly used criterion in producing concrete. However, the test on the compressive strength is complicated and time-consuming. More importantly, since the test is usually performed 28 days after the placement of the concrete at the construction site, it is too late to make improvements if unsatisfactory test results are incurred. Therefore, an accurate and practical strength estimation method that can be used before the placement of concrete is highly desirable. In this study, the estimation of the concrete strength is performed using support vector regression (SVR) based on the mix proportion data from two ready-mixed concrete companies. The estimation performance of the SVR is then compared with that of neural network (NN). The SVR method has been found to be very efficient in estimation accuracy as well as computation time, and very practical in terms of training rather than the explicit regression analyses and the NN techniques.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available