The Modeling Optimization For Boiler Based On Modified Fruit Fly Algorithm

Power plant boilers not only need a lot of coal resources,but also emit a lot of air pollutants.In the treatment of boiler efficiency and pollutant control on this issue,this paper compared with the method of boiler combustion optimization based on the improved algorithm of Drosophila traditional method has obvious characteristics,can provide reliable guidance for boiler efficiency and low pollution operation.In order to achieve goals which improve boiler efficiency and reduce NOx emission.On the basis of modified fruit fly optimization algorithm which is used to search the parameter of support vector machine(SVM)establishes emissions model.To solve the problem that the FOA has lower prediction accuracy and the slower convergence speed.We take advantage of three-dimensional optimization and adaptive variable step-size to modify the fruit fly optimization in this paper.And the completion of the penalty factor in SVM C,G kernel parameter and insensitive loss coefficient,the three parameter optimization.The model was established by the support vector machine(SVM)which effect of the boiler combustion model was the best.Using different sample data validated MFOASVM model,and compared with the prediction results which is forecasted by FOA-SVM.The results show that modified fruit fly algorithm has strong ability of parameter optimization.It increased effectively the level of the SVM model parameters optimization and improved the precision of optimization of the SVM model It compared with FOA-SVM which has higher prediction accuracy and faster convergence speed.MFOA-SVM can accurately predict the boiler thermal efficiency and NO_x emissions.In addition to the combustion model which is proposed as the foundation.Optimization of boiler based on MFOA algorithm.We use a multi-objective optimization method which based on single objective optimization.The simulation results show that the proposed combustion optimization scheme can effectively improve the boiler efficiency and reduce NO_x emissions.