An Application Of Hybrid Firefly And Pso With Support Vector Regression For Modeling A Clarifier Process In Sugar Industry

Abstract

In this paper, Support Vector Regression (SVR) with the Particle Swarm Optimization algorithm (PSO) and SVR with Firefly algorithm (FFA) is used to model the clarifier process of sugar industry. Generally, SVR model is involved in mapping the nonlinear structure for nonlinear regression. Hybrid structure of SVR with PSO-FFA is involved in the modeling of nonlinear process. The proposed method is has improved its efficient characteristics in the process of maintaining the neutralized value of pH. The performances of proposed methods are compared and the result were obtained which shows the effectiveness of the proposed hybrid algorithm. The results proves to be effective for using in the real-time complex industrial problems.