Research on Dissolve Oxygen Modeling Based on Neural Network
The structure, characteristics and principles of BP neural network model are described in this paper. First, three impact factors of the dissolved oxygen are selected as the sample input of network, and then the parameters of BP neural network are selected, such as network structure, learning algorithm, output layer transfer function, learning rate and so on. Finally, the BP neural network model is established and trained, in order to approach compensate the effects of improves non-linearity. The simulation results show that BP neural network is practical and dependable in the field of dissolved oxygen modeling and has nice applied prospect.
Jinglong Bu, Pengcheng Wang, Liqun Ai, Xiaoming Sang, Yungang Li
G. D. Gao et al., "Research on Dissolve Oxygen Modeling Based on Neural Network", Advanced Materials Research, Vols. 287-290, pp. 2640-2643, 2011