Risk prediction of traditional Chinese medicine decoction pieces production based on BP neural network
This article conducts an in-depth study on the risk issues in the production of traditional Chinese medicine decoction pieces,and utilizes BP neural networks to construct a risk prediction model.Through investigating a large amount of production data and selecting key variables,the model has demonstrated excellent performance when the number of hidden layer nodes is set to 14.After 11 iterations,the error value has significantly decreased,and the correlation coefficient is as high as 0.940 35,showing high fitting and generalization capabilities.Compared with traditional methods,this model can detect risks earlier,providing a new approach for risk prediction in the production of traditional Chinese medicine decoction pieces.It helps to improve production efficiency,reduce costs and minimize losses for enterprises,which is of great significance to the safe production of the traditional Chinese medicine decoction piece industry.
Chinese medicine decoction piecesProduction riskBP neural networkRisk prediction
NETL
NSTL
万方数据
