首页 | 官方网站   微博 | 高级检索  
     

数据驱动系统方法概述
引用本文:许建新,侯忠生.数据驱动系统方法概述[J].自动化学报,2009,35(6):668-675.
作者姓名:许建新  侯忠生
作者单位:1.新加坡国立大学电子与计算机工程系 新加坡 119260
基金项目:State Key Program of National Natural Science Foundation of China,国家自然科学基金 
摘    要:阐述了关于数据驱动系统方法的几点思考. 文中简要地探讨了以下三个主要问题: 离线数据与在线数据处理方法之间的演变关系, 数据驱动方法与基于模型的方法之间的优势互补关系, 以及数据驱动系统方法的前景. 在现有的知识和研究水平下给出数据驱动系统问题的解决方法是不切实际的. 针对控制、决策、调度和故障诊断, 本文的目的是对这四个领域的数据驱动方法问题进行归纳与分类, 并探讨可行的、有潜力的研究方向.

关 键 词:数据驱动    主要关系    问题分类    研究方向
收稿时间:2008-12-17
修稿时间:2009-3-9

Notes on Data-driven System Approaches
XU Jian-Xin HOU Zhong-Sheng.Notes on Data-driven System Approaches[J].Acta Automatica Sinica,2009,35(6):668-675.
Authors:XU Jian-Xin HOU Zhong-Sheng
Affiliation:1.Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore;2.Advanced Control Systems Laboratory, School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, P.R. China
Abstract:In this paper, we present several considerations centered around the data-driven system approaches. We briefly explore three main issues: the evolving relationship between off-line and on-line data processing methods, the complementary relationship between the data-driven and model-based methods, and the perspectives of data-driven system approaches. Instead of offering solutions to data-driven system problems, which is impossible at the present level of knowledge and research, in this article we aim at categorizing and classifying open problems, exploring possible directions that may offer alternatives or potentials for the four key fields of interests: control, decision making, scheduling, and fault diagnosis.
Keywords:Data-driven  principal relations  problem classification  research directions
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《自动化学报》浏览原始摘要信息
点击此处可从《自动化学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号