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Review of Artificial Neural Network and Its Application Research in Distillation
Author(s) -
Jing Sun,
Qi Tang
Publication year - 2021
Publication title -
journal of engineering research and reports
Language(s) - English
Resource type - Journals
ISSN - 2582-2926
DOI - 10.9734/jerr/2021/v21i317451
Subject(s) - artificial neural network , rectification , computer science , artificial intelligence , process (computing) , distillation , machine learning , control engineering , engineering , chemistry , organic chemistry , voltage , electrical engineering , operating system
With the development of rectification technology, the scale of its production equipment has continued to expand, and its calculation requirements have become more complex. The use of traditional optimized control methods can no longer meet the requirements. Artificial neural networks imitate the human brain for self-learning and optimization, intelligently process various complex information, and have been widely used in various chemical processes. Because the artificial neural network has the advantages of self-learning, associative storage, and high-speed search for optimized solutions, it can perform high-precision simulation and prediction of rectification operations, and has been widely used in the optimal control of rectification towers. This article gives a basic overview of artificial neural networks, and introduces the application research of artificial neural networks in distillation at home and abroad.

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