Review of Artificial Neural Network and Its Application Research in Distillation
Jing Sun *
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China.
Qi Tang
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China.
*Author to whom correspondence should be addressed.
Abstract
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.
Keywords: Artificial neural network, algorithm, distillation, application research