A Review of Artificial Neural Networks for Chemical Process Optimization and Compound Property Prediction
Lei Wang *
East China University of Science and Technology, Shanghai 200237, China.
Jiacong Kang
East China University of Science and Technology, Shanghai 200237, China.
*Author to whom correspondence should be addressed.
Abstract
Artificial neural networks are widely used in chemical processes because of their powerful data processing capabilities, fault tolerance, nonlinear relationship processing capabilities, and learning capabilities. This paper will introduce the development history and important models of artificial neural network, and focus on its application in chemical process optimization and prediction of physical properties of compounds.
Keywords: Artificial neural network, BP neural network, CNN, RBF, process optimization, property prediction