A COMPREHENSIVE STUDY ON THE CONCRETE COMPRESSIVE STRENGTH ESTIMATION USING ARTIFICIAL NEURAL NETWORK AND ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM
سال انتشار: 1395
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 46
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شناسه ملی سند علمی:
JR_IJOCE-7-1_005
تاریخ نمایه سازی: 5 آذر 1402
چکیده مقاله:
This research deals with the development and comparison of two data-driven models, i.e., Artificial Neural Network (ANN) and Adaptive Neuro-based Fuzzy Inference System (ANFIS) models for estimation of ۲۸-day compressive strength of concrete for ۱۶۰ different mix designs. These various mix designs are constructed based on seven different parameters, i.e., ۳/۴ mm sand, ۳/۸ mm sand, cement content, maximum size of aggregate, gravel content, water-cement ratio, and fineness modulus. In this study, it is found that the ANN model is an efficient model for prediction of compressive strength of concrete. In addition, ANFIS model is a suitable model for the same estimation purposes, however, the ANN model is recognized to be more fitting than ANFIS model in predicting the ۲۸-day compressive strength of concrete.
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