کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
259519 | 503637 | 2010 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of the compressive strength of no-slump concrete: A comparative study of regression, neural network and ANFIS models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی عمران و سازه
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چکیده انگلیسی
No-slump concrete (NSC) is defined as concrete having either very low or zero slump that traditionally used for prefabrication purposes. The sensitivity of NSC to its constituents, mixture proportion, compaction, etc., enforce some difficulties in the prediction of the compressive strength. In this paper, by considering concrete constituents as input variables, several regression, neural networks (NNT) and ANFIS models are constructed, trained and tested to predict the 28-days compressive strength of no-slump concrete (28-CSNSC). Comparing the results indicate that NNT and ANFIS models are more feasible in predicting the 28-CSNSC than the proposed traditional regression models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Construction and Building Materials - Volume 24, Issue 5, May 2010, Pages 709–718
Journal: Construction and Building Materials - Volume 24, Issue 5, May 2010, Pages 709–718
نویسندگان
Jafar Sobhani, Meysam Najimi, Ali Reza Pourkhorshidi, Tayebeh Parhizkar,