Application of Artificial Neural Network in Distillation System: A Critical Review of Recent Progress
Asian Journal of Research in Computer Science · pp. 8–16 · Published 9 Aug 2021
10.9734/ajrcos/2021/v11i130252Abstract
Distillation is a unit operation with multiple input parameters and multiple output parameters. It is characterized by multiple variables, coupling between input parameters, and non-linear relationship with output parameters. Therefore, it is very difficult to use traditional methods to control and optimize the distillation column. Artificial Neural Network (ANN) uses the interconnection between a large number of neurons to establish the functional relationship between input and output, thereby achieving the approximation of any non-linear mapping. ANN is used for the control and optimization of distillation tower, with short response time, good dynamic performance, strong robustness, and strong ability to adapt to changes in the control environment. This article will mainly introduce the research progress of ANN and its application in the modeling, control and optimization of distillation towers.
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Cited by 17
Haonan Wang, Yijia Chen · Asian Journal of Chemical Sciences · 2021
Mengyu Wang, Zhu Zhu · Asian Journal of Chemical Sciences · 2022
Jing Sun, Qi Tang · Journal of Engineering Research and Reports · 2021
Chunyu Wang, Lujie Wang · Journal of Engineering Research and Reports · 2023
Li Sun, Fei Liang, Wutai Cui · Asian Journal of Research in Computer Science · 2021
Haonan Wang, Yijia Chen · Asian Journal of Research in Computer Science · 2022
Bin Yang, Tinghuai Ma, Xuejian Huang · IEEE Access · 2023
Huihui Wang, Wenwen Luan, Li Sun · Chemical Engineering Research and Design · 2022
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