Volume 9, Issue 2 (4-2019)
2019, 9(2): 251-272 |
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Sharifi Y, Hosseinpour M. ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN. International Journal of Optimization in Civil Engineering 2019; 9 (2) :251-272
URL: http://ijoce.iust.ac.ir/article-1-387-en.html
URL: http://ijoce.iust.ac.ir/article-1-387-en.html
Abstract: (17121 Views)
In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training and testing state obtained from a reliable data base. Then, a comparison has been made between proposed ANFIS model and SR model to have an idea about the predictive power of these methods.
Keywords: adaptive neuro-fuzzy inference system (ANFIS), stepwise regression (SR), compressive strength of concrete, reliable modeling method, metakaolin.
Type of Study: Research |
Subject:
Applications
Received: 2018/10/3 | Accepted: 2018/10/3 | Published: 2018/10/3
Received: 2018/10/3 | Accepted: 2018/10/3 | Published: 2018/10/3
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