Adaptive Neuro-Fuzzy Inference System for Predicting Compressive Strength of Fibres Self Compacting Concrete

Abstract

This research focused on the applicability of Adaptive Network-Based Fuzzy Inference System (ANFIS) for predict the compressive strength of fibers self-compacting concrete. An ANFIS model combines the benefit of ANN and fuzzy logic. The data developed experimentally for fibers self-compacting concrete and the data sets of a total 99 concrete samples were used in this work. In this paper research is computational based for prediction of concrete compressive strength. A model was developed using ANFIS with five input nodes as w/p ratio, course aggregate, fine aggregate, fiber and superplastizers. In this model Feed-forward three-layer back-propagation neural networks with 10 hidden nodes were examined using learning algorithm. ANFIS model proposed analytically that gives more compatible results. Hence, the model is adopted to predict the strength of fibrous self-compacting concrete.