Modeling and optimization of polysaccharide precipitation of traditional Chinese medicine injection

This study investigates Ophiopogon japonicas, a traditional Chinese medicine, by establishing the process model of polysaccharide precipitation based on a neural network algorithm. First, the principle of the BP neural network and the selection method of the model parameters are discussed, and the improved BP neural network algorithm is proposed. Then, the BP neural network model based on the population genetic algorithm (PGA) is established by analyzing the precipitation process of Ophiopogon japonicus polysaccharide. The weights and thresholds are trained and optimized to improve the precision of the polysaccharide precipitation model. Finally, the effect of the algorithm is illustrated by numerical simulation, and the simulation results are analyzed. This work lays the foundation for the future control system design.