Study on Forecasting Ceramic Membrane Fouling in TCM Extracts Based on Improved BP Neural Network

VernacularTitle:基于改进BP神经网络的中药水提液陶瓷膜污染预测研究
Author: Pengwei DOU ; Zhen WANG ; Kankan SHE ; Wenling FAN
Keywords: TCM extracts; membrane fouling; BP neural network; hidden layer neuron; genetic algorithm
From: Chinese Journal of Information on Traditional Chinese Medicine 2017;24(4):92-96
CountryChina
Language:Chinese
Abstract: Objective To prevent and treat of ceramic membrane purification of membrane fouling process of TCM extracts; To explore new methods of forecasting membrane fouling degree.Methods BP neural network model was improved. Methods to fast determine the optimal number of neurons in the hidden layer and fast algorithm for optimizing the weight and threshold of BP neural network were studied. Data of 207 groups of TCM extracts were under network training and prediction.ResultsCompared with the models of multiple regression analysis, basic BP neural network and RBF neural network, the error of the improved BP neural network model was less than that of the BP neural network model, and the mean square error was only 0.0057. In addition, the improved BP neural network model performance was more stable. In the 20 random running experiments, the goal of the success rate achieved up to 95%.Conclusion The improved model has a good network performance, the fitting effect and prediction ability, and can forecast the fouling degree of membrane stably and accurately.