Studies on Pumice Lightweight Aggregate Concrete with Quarry Dust Using Mathematical Modeling Aid of ACO Techniques

The lightweight aggregate is an aggregate that weighs less than the usual rock aggregate and the quarry dust is a rock particle used in the concrete for the experimentation. The significant intention of the proposed technique is to frame a mathematical modeling with the aid of the optimization techniques. The mathematical modeling is done by minimizing the cost and time consumed in the case of extension of the real time experiment. The proposed mathematical modeling is utilized to predict four output parameters such as compressive strength (Mpa), split tensile strength (Mpa), flexural strength (Mpa), and deflection (in mm). Here, the modeling is carried out with three different optimization techniques like genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) with 80% of data from experiment utilized for the training and the remaining 20% for the validation. Finally, while testing, the error value is minimized and the performance obtained in the ACO for the parameters such as compressive strength, split tensile strength, flexural strength, and deflection is 91%, 98%, 87%, and 94% of predicted values, respectively, in the mathematical modeling.