Neural Network Algorithm and Its Application in Supercritical Extraction Process
Yu Qi *
School of Chemical Engineering, East China University of Science and Technology, Shanghai,200237, China.
Zhaolan Zheng
School of Chemical Engineering, East China University of Science and Technology, Shanghai,200237, China.
*Author to whom correspondence should be addressed.
Abstract
Artificial neural network （ANN）algorithms can be used for multi-parameter optimization and control by simulating the mechanisms of the human brain. Therefore, ANN is widely used in many fields such as signal processing, intelligent driving, face recognition, and optimization and control of chemical processes. As a green and efficient chemical separation process, supercritical extraction is especially suitable for the separation and purification of active ingredients in natural substances. Because there are many parameters that affect the separation efficiency of the process, the neural network algorithm can be used to quickly optimize the process parameters based on limited experimental data to determine the appropriate process conditions. In this work, the research progress of neural network algorithms and supercritical extraction are reviewed, and the application of neural network algorithms in supercritical extraction is discussed, aiming to provide references for researchers in related fields.
Keywords: Artificial neural network algorithm, BP neural network, RBF neural network, supercritical fluid extraction.