Application Progress of Artificial Neural Network in Chemical Industry
Xindi Feng
School of Chemical Engineering, East China University of Science and Technology, Shanghai - 200237, China.
Li Sun *
School of Chemical Engineering, East China University of Science and Technology, Shanghai - 200237, China.
*Author to whom correspondence should be addressed.
Abstract
The design and optimization of chemical equipment and devices and the control of chemical processes involve many factors and are very complex. The traditional methods and technologies cannot obtain satisfactory results. Artificial neural network technology has the ability to deal with complex objects and has been widely used in various engineering fields including chemical industry. In this paper, the research progress of artificial neural network in chemical industry is reviewed. The application progress of artificial neural network in signal peak recognition, catalyst optimization, industrial process, reaction process, physical data and other aspects is summarized. The advantages and limitations of artificial neural network in chemical industry are analyzed. Finally, the development trend of its application in chemical industry is prospected.
Keywords: Artificial neural network, reaction process, catalyst selection, physical properties data