Artificial Neural Network and Its Application Research Progress in Chemical Process
Asian Journal of Research in Computer Science · pp. 177–185 · Published 23 Dec 2021
10.9734/ajrcos/2021/v12i430302Abstract
Most chemical processes, such as distillation, absorption, extraction, and catalytic reactions, are extremely complex processes affected by multiple factors. As a result, the relationships between their input and output variables are non-linear, and it is not easy to optimize or control them using traditional methods. Artificial neural network is a systematic structure composed of multiple neuron models. By simulating many basic functions of the nervous system of living organisms, nonlinear control can be realized without relying on mathematical models, and it is especially suitable for more complex control objects. This article will introduce artificial neural networks' basic principles and development history, and review its application research progress in chemical process control, fault diagnosis, and process optimization.
Cited by 16
Jing Sun, Qiong Chen · Asian Journal of Chemical Sciences · 2022
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Xinyi Yang, Fenxiao Chen · Asian Journal of Advanced Research and Reports · 2024
Zhihui Zhao, Jiying Li · Journal of Engineering Research and Reports · 2022
Devika P. Vala, S. B. Gajjar, D. Tipre · World Journal of Microbiology & Biotechnology · 2026
Jianan Zhao, Geng Tian, Wei Yang · Computers and Chemical Engineering · 2026
R. Nicholas, Enrico Deccen Aristan, Angeline Rachel · 2025 2nd Beyond Technology Summit on Informatics International Conference (BTS-I2C) · 2025
R. Bonal · Neural computing & applications (Print) · 2025
Afrânio Melo, M. Câmara, J. C. Pinto · Processes · 2024
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