دوره 1، شماره 1 - ( 12-1389 )                   جلد 1 شماره 1 صفحات 209-189 | برگشت به فهرست نسخه ها

XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Muthupriya P, Subramanian K, Vishnuram B. PREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS. International Journal of Optimization in Civil Engineering 2011; 1 (1) :189-209
URL: http://ijoce.iust.ac.ir/article-1-15-fa.html
PREDICTION OF COMPRESSIVE STRENGTH AND DURABILITY OF HIGH PERFORMANCE CONCRETE BY ARTIFICIAL NEURAL NETWORKS. عنوان نشریه. 1389; 1 (1) :189-209

URL: http://ijoce.iust.ac.ir/article-1-15-fa.html


چکیده:   (27326 مشاهده)
Neural networks have recently been widely used to model some of the human activities in many areas of civil engineering applications. In the present paper, artificial neural networks (ANN) for predicting compressive strength of cubes and durability of concrete containing metakaolin with fly ash and silica fume with fly ash are developed at the age of 3, 7, 28, 56 and 90 days. For building these models, training and testing using the available experimental results for 140 specimens produced with 7 different mixture proportions are used. The data used in the multi-layer feed forward neural networks models are designed in a format of eight input parameters covering the age of specimen, cement, metakaolin (MK), fly ash (FA), water, sand, aggregate and superplasticizer and in another set of specimen which contain SF instead of MK. According to these input parameters, in the multi-layer feed forward neural networks models are used to predict the compressive strength and durability values of concrete. It shown that neural networks have high potential for predicting the compressive strength and durability values of the concretes containing metakaolin, silica fume and fly ash.
متن کامل [PDF 516 kb]   (8843 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: Optimal design
دریافت: 1390/8/2 | انتشار: 1389/12/24

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به دانشگاه علم و صنعت ایران می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb