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Multi-Objective Optimum Design for Wave-Plate Demister Based on NSGA-ΙΙ Algorithm

For optimizing the structure design of the wave-plate demister vanes in wet flue gas desulfurization system (WFGD) of power plants, the characteristics models of removal efficiency and pressure drop were established by using least squares support vector machine (LSSVM) based on numerical simulation results. The highest relative error between the predicted output and measured value is 2%, it proves the modeling is good for the prediction. Based on the characteristics models, a multi-objective optimization model was established. It used the structural parameters as the optimal variables and the demister characteristics as the objective function. This optimization model was solved by non dominated sorting genetic algorithm (NSGA-II). The simulation data show that the Multi-objective optimum method can get more effective results compared to the weight coefficient method.