Modeling liquid phase oxygenation process using neural network

This paper describes a modeling application for LPO (liquid phase oxygenation) process using backpropagation neural network. An integrated neural professional II^TM based software for developing neural network models is developed for this project. In this software, a visual data processing method for improving the effects of training, a correlation analyzer that can be used to help simplify the model´s inputs/outputs structure and a training kit are all included. The satisfactory result is reached by selecting different structures and variables of the neural networks. At last, an online upgrading scheme is proposed and has shown the great potential in simulation