Abstract
In the Research of prediction of Membrane Bio-Reactor (MBR) Membrane Fouling, we have used Simulated Annealing (SA) and support vector machine (SVM) [9][10] to establish the model to predict MBR Membrane Fouling[1]. An experimental research demonstrates that SVM model based on SA (SA-SVM) has better predicted precision than SVM model based on Genetic Algorithm (GA-SVM). However, in the process of optimization parameters of predictive model of MBR membrane fouling model using SA, we found that SA has two problems: a slowness of convergence rate and the parameters selection is sensitive. Therefore, we introduce a Genetic Algorithm (GA) and combine SA with the GA, Adaptive Simulated Annealing Genetic Algorithm (ASAGA), to optimize the input data of MBR Membrane Fouling predictive model. This algorithm remains both the strong global searching ability of GA and the good local searching ability of SA. Calculation shows that the ASAGA-SVM predictive model of MBR Membrane Fouling matches well and higher predictive precision than SA-SVM predictive model of MBR Membrane Fouling.
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