Application of ANN and ANFIS Models in Determining Compressive Strength of Concrete

Journal of Soft Computing in Civil Engineering

关键词: Compressive strength;    Artificial Neural Network;    Adaptive Neuro Fuzzy Inference System;    Prediction models;   

DOI  :  10.22115/scce.2018.51114

学科分类：工程和技术（综合）

来源: Pouyan Press

【 摘 要 】

Concrete compressive strength is recognized as one of the most important mechanical properties of concrete and one of the most significant mechanical properties in determining the quality of the produced concrete. Since the traditional procedures of determining the compressive strength of concrete require time and cost, scholars have always been looking for new methods to replace them with existing traditional methods. In this paper, soft computing methods are investigated for determining the compressive strength of concrete. To be specific, 150 different concrete specimens with various mix design parameters have been built in the laboratory, and the compressive strength of them have been measured after 28 days of curing in the water. Five different concrete mix parameters, (i.e. cement, water to cement ratio, gravel, sand, and microsilica) were considered as input variables. In addition, two soft computing techniques have been used in this study which are Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference (ANFIS) System. Results have shown that both of ANN and ANFIS models are successful models for predicting the compressive strength of concrete. Also, results have shown that ANFIS is more capable than ANN in predicting the compressive strength of concrete.

【 授权许可】

CC BY