Neural Network Algorithm and Its Application in Supercritical Extraction Process
Asian Journal of Chemical Sciences · pp. 19–28 · Published 13 Jan 2021
10.9734/ajocs/2021/v9i119062Abstract
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.
Cited by 7
Peijun Guo, Zefeng Wu · International Conference on Artificial Intelligence and Soft Computing · 2023
Mengyu Wang, Zhu Zhu · Asian Journal of Chemical Sciences · 2022
Po Li, Zaoyong Lu · Asian Journal of Research in Computer Science · 2022
Zhiqiang Liu, Wentao Zhou · Asian Journal of Chemical Sciences · 2021
Li Sun, Fei Liang, Wu Cui · Asian Journal of Research in Computer Science · 2021
Zhiqiang Liu, Wentao Zhou · arXiv.org · 2021
Jing Sun, Qi Tang · arXiv.org · 2021
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