Modeling study of sludge process based on neural network

Abstract

On the basis of analyzing the classical methods of sludge process modeling, the paper put forward a new method about activated sludge process by neural networks. Firstly, the paper utilized principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors. Then built activated sludge process system by BP and RBF artificial neural networks, the applicability of the two neural network models were analyzed to sludge process. The experiment result shows that: (1) these neural networks may reflect real conditions correctly and have strong self-adaptation; (2) the RBF neural network model has better convergence ability and impending speed than the BP neural network model.