Research Progress in the Application of Artificial Neural Networks in Catalyst Optimization

Abstract

The catalyst can speed up the chemical reaction and increase the selectivity of the target product, playing an important role in the chemical industry. By improving the performance of the catalyst, the economic benefits can be greatly improved. Artificial Neural Network (ANN), as one of the most popular machine learning algorithms, has parallel processing and self-learning capabilities as well as good fault tolerance, and has been widely used in various fields. By optimizing the catalyst through ANN, time and resource consumption can be greatly reduced, and greater economic benefits can be obtained. This article reviews how CNN technology can help people solve highly complex problems and accelerate progress in the catalytic world.

Optimization of Extraction Process Based on Neural Network

“…In the field of construction engineering, artificial neural networks are used to predict concrete strength and find the nonlinear input-output relationship between concrete strength and its influencing factors [9,10]. In addition, artificial neural networks are used in the field of plant diseases control [11][12][13], process control and optimization [14][15][16], troubleshooting [17][18][19], intelligent control of industrial product assembly line [20][21][22], robotic surgery [23][24][25], intelligent driving [26][27][28], chemical product development [29][30][31], signal processing [32][33][34], and so on.…”

Catalyst Optimization Design Based on Artificial Neural Network

“…A network with a small central layer is used to reconstruct highdimensional input vectors [12], which has led to a boom in the application of deep learning in various scenarios. So far, ANN has been successfully applied to intelligent driving [13][14][15], aerospace [16,17], signal processing [18][19][20], process control and optimization [21][22][23], safety protection [24][25][26], image processing [27][28][29], forest pest protection [30,31], time series forecasting [32][33][34] and so on.…”

Research Progress of Chemical Process Control and Optimization Based on Neural Network

“…In 2016, the emergence of AlphaGo brought people's research enthusiasm for deep learning to a new height. So far, artificial neural networks have been widely used in various fields, such as deep learning and game theory [21][22][23], process control and optimization [24][25][26], face recognition [27][28][29], forecasting [30][31][32], fault detection [33][34][35], image processing [36][37][38] and other fields [39,40]. The application of artificial neural network in the field of chemical process control and optimization will be reviewed below.…”