Multi-index optimization of water extraction process of Siwu Decoction by BP neural network combined with entropy weight method / 中草药

ABSTRACT

Objective: To optimize the water extraction process of Siwu Decoction by BP neural network combined with orthogonal experiment. Methods: The water amount, the extraction time, and the extraction times were taken as factors. Entropy weight method was used to calculate the comprehensive scores of the multi-indicators of eight active components of 5-hydroxymethylfurfural, chlorogenic acid, caffeic acid, paeoniflorin, ferulic acid, verbascoside, senkyunolide A, and ligustilide in R language environment. Using comprehensive score as an evaluation indicator, the BP neural network model was established by orthogonal experiment design, and the optimal water extraction process of Siwu Decoction was predicted through network training. Results: The optimized extraction process of Siwu Decoction was carried out by adding 8 times of water and extracting 3 times for 1 h. The relative error between the network predicted value and the actual measured value of the test sample was less than 1%. Conclusion: The established mathematical model can analyze and predict the water extraction process of Siwu Decoction. The obtained process is stable and feasible, and can effectively extract the active ingredients in Siwu Decoction.