Application of Multiple Linear Regression Models and Adaptive Neuro-Fuzzy Inference System Models to estimate the Compressive Strength of Concrete

The most widely used composite construction material is concrete. Compressive strength is an important monitoring parameter for quality assurance at construction site. In this paper,two different models of Multiple Linear Regression ( MLR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are developed to predict the 28 day compressive strength of concrete using the experimental datasets available . These two models are compared . Sensitivity Analysis (SA) is carried out for two different sets of parameters. ANFIS models predict more effectively as their coefficients of multiple determination(R Square) are higher than those of MLR models. This shows that the nonlinear correlation among input variables is better represented in ANFIS models than in MLR models .Goal 12 of United Nations Sustainable Development deals with the sustainable consumption and production patterns and it is taken into account as environmentally degrading materials( flyash and blast furnace slag ) are used.