Application Progress of Artificial Neural Network in Chemical Industry

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.

A Review of Artificial Neural Networks for Chemical Process Optimization and Compound Property Prediction

“…So far, artificial neural network has been widely used in various fields, mainly including intelligent driving [18,19], auxiliary medical treatment [20,21], voice information processing [22,23], Chinese medicine processing [24,25], chemical process optimization and process control [26][27][28].…”

Research Progress of Artificial Neural Network and Its Application in Fault Diagnosis of Chemical Industry

“…Artificial neural network is a non-procedural, adaptive, brain-type information processing, and its essence is a parallel distributed information processing function through network transformation and dynamic behavior, and imitates human's brain and nerves carry out information processing systems" [21,22]. "It touches various fields of neuroscience, mind science, artificial intelligence, computer science and other interdisciplinary fields" [23][24][25][26][27]. "Artificial neural network is a parallel distributed system, which adopts a completely different mechanism from traditional artificial intelligence and information processing technology, overcomes the shortcomings of traditional logic-based artificial intelligence in processing intuition and unstructured information, and has adaptive, selforganizing and real-time learning features" [28].…”