Artificial Neural Network and its Application Research Progress in Distillation
This is an incremental review paper summarizing existing ANN applications in distillation for the chemical engineering field.
This paper reviews how artificial neural networks (ANNs) are applied to distillation processes in chemical engineering, highlighting their ability to make high-precision simulation predictions due to advantages like self-learning and optimized solution search.
Artificial neural networks learn various rules and algorithms to form different ways of processing information, and have been widely used in various chemical processes. Among them, with the development of rectification technology, its production scale continues to expand, and its calculation requirements are also more stringent, because the artificial neural network has the advantages of self-learning, associative storage and high-speed search for optimized solutions, it can make high-precision simulation predictions for rectification operations, so it is widely used in the chemical field of rectification. 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.