Artificial Neural Networks and Its Applications in Chemical Industry

Abstract

Artificial neural networks, as an important part of artificial intelligence, have a wide scope of development to improve the traditional production technology of chemical processes with its inherent advantages of parallel structure and parallel processing, fault tolerance, full approximation of any complex nonlinear relationships, learnability and self-adaptability, etc. Thus, it has a wide scope of development to improve the problems of lagging diagnosis, difficult to optimize control, large errors in physical property estimation and inability to deal with nonlinear complex situations. This paper summarizes the theory of artificial neural network, including its structure and characteristics, and introduces its applications in different fields, especially in chemical industry.