深度学习在流程工业过程数据建模中的应用

袁小锋; 王雅琳; 阳春华; 桂卫华

doi:10.11959/j.issn.2096-6652.202012

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深度学习在流程工业过程数据建模中的应用

综述与展望 | 更新时间：2024-06-05

- 深度学习在流程工业过程数据建模中的应用
- The application of deep learning in data-driven modeling of process industries
- 智能科学与技术学报 2020年2卷第2期页码：107-115
- 作者机构：
- 作者简介：
  
  [ "袁小锋（1988- ），男，博士，中南大学自动化学院副教授，主要研究方向为工业大数据与人工智能、深度学习与模式识别、过程监测与软测量建模等" ]
  [ "王雅琳（1973- ），女，博士，中南大学自动化学院教授、副院长、博士生导师，主要研究方向为大数据分析与处理、智能集成建模、过程监测与故障诊断等" ]
  [ "阳春华（1965- ），女，博士，中南大学自动化学院教授、院长、博士生导师，主要研究方向为复杂工业过程建模与优化、分析检测与自动化装置、智能化系统等" ]
  [ "桂卫华（1950- ），男，中国工程院院士，中南大学自动化学院教授，主要研究方向为工业大系统递阶和分散控制理论及应用、复杂工业过程建模、优化与控制应用和知识自动化" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2018YFB1701100);国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2018AAA0101603);国家自然科学基金资助项目;The National Natural Science Foundation of China(61703440);国家自然科学基金资助项目;The National Natural Science Foundation of China(61590921);111引智项目;The 111 Project(B17048);中南大学创新驱动计划基金资助项目;Innovation Driven Program of Central South University(2018CX012);湖南省自然科学基金资助项目;The Natural Science Foundation of Hunan Province of China(2018JJ3687)
- DOI：10.11959/j.issn.2096-6652.202012
  中图分类号： TP18
- 网络出版日期：2020-06，
  
  纸质出版日期：2020-06-20
- 稿件说明：
移动端阅览
袁小锋, 王雅琳, 阳春华, 等. 深度学习在流程工业过程数据建模中的应用[J]. 智能科学与技术学报, 2020,2(2):107-115.

Xiaofeng YUAN, Yalin WANG, Chunhua YANG, et al. The application of deep learning in data-driven modeling of process industries[J]. Chinese journal of intelligent science and technology, 2020, 2(2): 107-115.
袁小锋, 王雅琳, 阳春华, 等. 深度学习在流程工业过程数据建模中的应用[J]. 智能科学与技术学报, 2020,2(2):107-115. DOI： 10.11959/j.issn.2096-6652.202012.

Xiaofeng YUAN, Yalin WANG, Chunhua YANG, et al. The application of deep learning in data-driven modeling of process industries[J]. Chinese journal of intelligent science and technology, 2020, 2(2): 107-115. DOI： 10.11959/j.issn.2096-6652.202012.

摘要

深度学习是近年来发展的人工智能技术。相比于传统浅层学习模型，深度学习具有强大的特征表示和函数拟合能力。深度学习能够从海量数据中提取层次特征，其在流程工业过程数据驱动建模中具有较大的潜力和应用前景。首先简单介绍了深度学习的发展历程；然后，介绍了4类广泛使用的深度学习模型以及它们在流程工业过程数据建模中的应用；最后，在流程工业过程数据建模领域对深度学习进行了简要总结。

Abstract

Deep learning is an artificial intelligence technique developed in recent years.Compared with traditional shallow models

deep learning has a strong ability of feature representation and function fitting.It can extract hierarchical features from massive data

which has great potential for data-driven modeling in process industries.Firstly

the history of deep learning was introduced.Then

four widely used deep networks and their applications were introduced in data-driven modeling of process industries.At last

the conclusions about deep learning and its applications in process in dustries were given.

关键词

Keywords

references

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