MODELING FLEXURAL STRENGTH OF EPS LIGHTWEIGHT CONCRETE USING REGRESSION, NEURAL NETWORK AND ANFIS
عنوان مقاله: MODELING FLEXURAL STRENGTH OF EPS LIGHTWEIGHT CONCRETE USING REGRESSION, NEURAL NETWORK AND ANFIS
شناسه ملی مقاله: JR_IJOCE-9-2_008
منتشر شده در در سال 1398
شناسه ملی مقاله: JR_IJOCE-9-2_008
منتشر شده در در سال 1398
مشخصات نویسندگان مقاله:
J. Sobhani
M. Ejtemaei
A. Sadrmomtazi
M. A. Mirgozar
خلاصه مقاله:
J. Sobhani
M. Ejtemaei
A. Sadrmomtazi
M. A. Mirgozar
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 ۳۰۰-۲۰۰۰ kg/m۳. 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.
کلمات کلیدی: EPS concrete, silica fume, flexural strength, modeling, regression, neural network, ANFIS.
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1831288/