A new growing self-organizing neuron-fuzzy network with application to wastewater treatment
Qiao Jun-fei, Honggui Han · 2008
A new neural fuzzy algorithm based on the method of growing self-organizing network is proposed in this paper. Then the fuzzy rules can be changed on-line, it takes the experience out of the necessary side for the number of the fuzzy rules. A novel learning algorithm based on dynamic descent gradient is also presented. The main salient characters of the algorithm in this paper are: 1) a new method resolves the problem of the conventional neural network which can’t change the structure of the network; 2) the neurons of the neural network can be changed on-line; 3) a new method for the fast learning speed can be own. This new algorithm can be used to control the dissolved oxygenic in the wastewater treatment process. The results of the experiments prove the superiority of this algorithm compared with the conventional neural fuzzy algorithm.