The study of membrane fouling modeling method based on support vector machine for sewage treatment membrane bioreactor

The membrane bioreactor(MBR) ia a new technology of sewage treatment combining the membrane with the bioreactor, but the membrane fouling is an important factor to limit the MBR further development. Considering the issues that the relationship between the membrane fouling and affecting factors is a complicated and nonlinear, a modeling method based on support vector machine(SVM) is presented in this paper. The main parameters of affecting MBR membrane fouling is studied. The SVM network structure for membrane fouling is established. Moreover, we propose a self-adaptive parameter adjust iterative algorithm to confirm SVM parameters, thereby enhancing the converging speed and the predicting accuracy. With the ability of strong self-learning and well generalization of SVM, the modeling method can detect and assesse the membrane fouling degree of MBR in real time by learning the membrane fouling information. The detection results show that this method is feasible and effective.