Forecasting Pollution Using Numerical Simulation Implementing Artificial Bee Colony Optimization

Abstract

In this article, an optimization strategy is presented for the numerical solution of Burgers’ equations, which play an important role in estimating and forecasting pollution. The method involves the exponential B-spline basis function as the basis function in the differential quadrature method. Since exponential B-spline involves a parameter, the artificial bee colony optimization algorithm is implemented to find the unknown parameters that result in the minimum error. Among the metaheuristic optimization algorithms, the artificial bee colony (ABC) is one that has received the greatest attention from researchers and has been successfully implemented to solve various problems in engineering and sciences. The proposed work emphasizes the calculation of the parameter of exponential basis functions, a major factor that plays a role in the error calculation using the ABC optimization algorithm. The acquired findings are provided as tables, and the physical behaviour is showcased in the form of figures and tables. The results are in good conformity with the earlier studies.