化工进展2016，Vol.35Issue(12)：3755-3762,8.DOI:10.16085/j.issn.1000-6613.2016.12.004
人工神经网络在化工过程中的应用进展
Progress on the application of artificial neural network in chemical industry
宋泓阳 1孙晓岩 1项曙光1
作者信息
- 1. 青岛科技大学过程系统工程研究所，山东青岛266042
- 折叠
摘要
Abstract
Artificial neural networks were the important part of artificial intelligence,which had a broad space in improving the chemical process of traditional production techniques diagnosis of lag, difficult to optimize and control,large property estimation error and could not deal with complex nonlinear problems. Artificial neural networks have drawn much attention because of superior robustness,fault tolerance,approximation of complex nonlinear correlations,parallel processing and adaptive learning. Artificial neural networks have been applied to chemical processes in the following areas:fault diagnosis,process control and optimization,quality control,quantitative structure-activity/ property correlation analysis,property estimation,expert system and clustering analysis. This paper summarized the theory and development history of artificial neural network,and conducted meta-analysis of the literature on the principles and the development of artificial neural networks in chemical processes. Finally,the paper pointed out that the deep learning algorithm had advantages of high-performance and high speed,and then discussed that the future study of neural networks in chemical process would be the direction and hot topic in the development and application of deep learning algorithm.关键词
神经网络/模型/化工过程/生产/原理Key words
neural networks/model/chemical engineering process/production/principle分类
化学化工引用本文复制引用
宋泓阳,孙晓岩,项曙光..人工神经网络在化工过程中的应用进展[J].化工进展,2016,35(12):3755-3762,8.
