• CHIDOZIE CHUKWUEMEKA NWOBI-OKOYE
• IKECHUKWU ETIENNE UMEONYIAGU

In this study an adaptive neuro-fuzzy inference system (ANFIS) was used to predict the compressive strength of concrete produced with diesel contaminated sand. Concrete produced using sand contaminated with diesel at 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 5 and 10 percent were each cured for 7, 14, 28, 58, 90 and 118 days. The compressive strength of the concretes were measured for each percentage contamination and curing days. Subsequently, an ANFIS model was developed and used to predict the compressive strength of the concrete. The ANFIS model predictions with a correlation coefficient (R) of 0.9877 predicted better than a fuzzy logic (FL) model which predicted with R value of 0.9086. The results show that ANFIS model could be used to predict the compressive strength of concretes produced with diesel contaminated sand.

Neural-Fuzzy; Concrete; Diesel; Compressive Strength; Modelling

"Neuro-Fuzzy Model for Modelling the Effects of Petroleum Product Contaminated Sand on the Compressive Strength of Concretes Using: A Case Study of Diesel", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 11, page no.143-149, November-2017, Available :http://www.jetir.org/papers/JETIR1711025.pdf

"Neuro-Fuzzy Model for Modelling the Effects of Petroleum Product Contaminated Sand on the Compressive Strength of Concretes Using: A Case Study of Diesel", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 11, page no. pp143-149, November-2017, Available at : http://www.jetir.org/papers/JETIR1711025.pdf