Catalyst Optimization Design Based on Artificial Neural Network

Abstract

Artificial neural network (ANN) has the characteristics of self-adaptation, self-learning, parallel processing and strong nonlinear mapping ability. Compared with traditional experimental analysis modeling, ANN has obvious advantages in dealing with multivariable nonlinear complex relationships in the process of industrial catalyst design. In the face of the complex structure of catalyst, the unclear reaction mechanism and conditions, the use of neural network for small-scale experimental data analysis can save the time and energy invested in large-scale experimental research and obtain more perfect results in catalyst formulation optimization and condition selection. This paper summarizes the development of artificial neural network. The application principle, construction method and research progress of BP artificial neural network model in catalyst optimization design are summarized and analyzed. The development and innovation of artificial neural network in the future, as well as its continuous application and accumulation, will provide a powerful tool for the research of catalyst design and optimization in the future.

Advances in Neural Networks for Pharmaceutical Applications

“…In 2016, the advent of AlphaGo brought research enthusiasm for deep learning to a new height. Now ANN has been widely applied in various fields, such as image recognition [6][7][8], wireless signal processing [9][10][11][12], chemical process control and optimization [13][14][15][16], forecasting [17,18], security risk assessment [19], traditional Chinese medicine processing [20][21][22], aquatic products [23], intelligent driving [24,25], and so on.…”

Application of Artificial Neural Networks for Chemical Industry Safety Production: A Review

“…Artificial neural networks, like other machine learning methods, have been used to solve various problems in production and practical applications, such as process control and optimization [5][6][7], image recognition and single processing [8][9][10], forecasting [11,12], traditional Chinese medicine processing [13][14][15], aquatic products [16,17], security risk assessment [18,19], intelligent driving [20][21][22], and so on [23][24][25][26].…”