Optimization of extraction and purification processes of six flavonoid components from Radix Astragali using BP neural network combined with particle swarm optimization and genetic algorithm

Artificial neural network model- and response surface methodology-based optimization of Atractylodis Macrocephalae Rhizoma polysaccharide extraction, kinetic modelling and structural characterization

“…Reflux extraction is the process of combining herbs and solvents and heating them in a water bath at a steady temperature or using a heating apparatus so that the herbs' active components gradually dissolve into the solvent. This method works well for herbs with easily soluble components [34] , [35] . Compared with reflux extraction, the other two methods noted above are suitable for herbs that are unstable under heating conditions.…”

“…The BP neural network, GA-BP neural network, and GA-ACO-BP neural network were used to train, fit, and find the best process conditions. The performance of the model was evaluated by the coefficient of determination (R 2 ), mean absolute error (MAE), and root mean square error (RMSE), which were calculated with the following formulas [25] , [26] : where is the predicted value of each model, is the actual value, and is the average of the dataset. RSS, ESS, and TSS denote the regression sum of squares, residual sum of squares, and total sum of squares, respectively.…”

Research on artificial neural networks to accurately predict element concentrations in nutrient solutions

“…The BP-ANN is easy to jump to the local minimum in the training process, which reduces the convergence and generalization ability, so it is necessary to optimize the algorithm to improve the generalization ability [33]. Traditional RBF-ANN parameter optimization methods adopt gradient descent algorithm, etc, and the parameters obtained may not be the best [34].…”

Optimization of tetrastigma hemsleyanum extraction process based on GA-BPNN model and analysis of its antioxidant effect

“…Most current THR studies focus on components such as polysaccharide extracts [ 19 ], and there are relatively few studies on flavonoid extraction and antioxidant activity in vivo and in vitro; however, the potential antioxidant properties of dietary flavonoids have received much attention in recent years. Due to the limitations of the traditional response surface methodology (RSM), several researchers have developed genetic algorithm-back propagation neural network (GA-BPNN) models to optimize the extraction of active ingredients in Chinese medicine [ 20 , 21 ]. As a result, optimizing the extraction process of THR flavonoid components and studying network pharmacology on the antioxidant activity can not only provide a novel idea for the study of THR's pharmacological mechanism but also have important implications for future research on THR's antioxidant mechanism.…”