Volume 9, Issue 2 (4-2019)
IJOCE 2019, 9(2): 313-329 |
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Sobhani J, Ejtemaei M, Sadrmomtazi A, Mirgozar M A. MODELING FLEXURAL STRENGTH OF EPS LIGHTWEIGHT CONCRETE USING REGRESSION, NEURAL NETWORK AND ANFIS. IJOCE 2019; 9 (2) :313-329
URL: http://ijoce.iust.ac.ir/article-1-392-en.html
URL: http://ijoce.iust.ac.ir/article-1-392-en.html
Abstract: (17116 Views)
Lightweight concrete (LWC) is a kind of concrete that made of lightweight aggregates or gas bubbles. These aggregates could be natural or artificial, and expanded polystyrene (EPS) lightweight concrete is the most interesting lightweight concrete and has good mechanical properties. Bulk density of this kind of concrete is between 300-2000 kg/m3. In this paper flexural strength of EPS is modeled using four regression models, nine neural network models and four adaptive Network-based Fuzzy Interface System model (ANFIS). Among these models, ANFIS model with Bell-shaped membership function has the best results and can predict the flexural strength of EPS lightweight concrete more accurately.
Keywords: EPS concrete, silica fume, flexural strength, modeling, regression, neural network, ANFIS.
Type of Study: Research |
Subject:
Applications
Received: 2018/12/17 | Accepted: 2018/12/17 | Published: 2018/12/17
Received: 2018/12/17 | Accepted: 2018/12/17 | Published: 2018/12/17
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