Application of Artificial Neural Network in Simulation of Supercritical Extraction of Valerenic Acid from Valeriana officinalis L.

Abstract

Application of artificial neural network (ANN) has been studied for simulation of the extraction process by supercritical CO 2 . Supercritical extraction of valerenic acid from Valeriana officianalis L. has been studied and simulated according to the significant operational parameters such as pressure, temperature, and dynamic extraction time. ANN, using multilayer perceptron (MLP) model, is employed to predict the amount of extracted VA versus the studied variables. Three tests, validation, and training data sets in three various scenarios are selected to predict the amount of extracted VA at dynamic time of extraction, working pressure, and temperature values. Levenberg-Marquardt algorithm has been employed to train the MLP network. The model in first scenario has three neurons in one hidden layer, and the models associated with the second and the third scenarios have four neurons in one hidden layer. The determination coefficients are calculated as 0.971, 0.940, and 0.964 for the first, second, and the third scenarios, respectively, demonstrating the effectiveness of the MLP model in simulating this process using any of the scenarios, and accurate prediction of extraction yield has been revealed in different working conditions of pressure, temperature, and dynamic time of extraction.

Modeling of agarwood oil compounds based on linear regression and ANN for oil quality classification

“…Currently, the MLP network has widely used among the researcher in any areas of studies such as in grading the essential oil, pattern recognition, oil industry and many others [16]- [23]. MLP successfully implement in estimating the extraction yield on Oregano and Valerian essential oil [16], [17]. Researcher [17] used training algorithms; SCG, RBP, LM and Gradient Descent, while researcher [16] only used LM algorithm.…”

“…MLP successfully implement in estimating the extraction yield on Oregano and Valerian essential oil [16], [17]. Researcher [17] used training algorithms; SCG, RBP, LM and Gradient Descent, while researcher [16] only used LM algorithm. The only similarities in both research studies are the results obtained showed that LM algorithm performed good accuracy with minimum error.…”