Guest editorial: Special section on data-driven approaches for complex industrial systems

A1 Journal article (refereed)

Internal Authors/Editors

Publication Details

List of Authors: Zhiwei Gao, Henrik Saxen, Chuanhou Gao
Publication year: 2013
Journal: IEEE Transactions on Industrial Informatics
Journal acronym: IEEE T IND INFORM
Volume number: 9
Issue number: 4
Start page: 2210
End page: 2212
Number of pages: 3
ISSN: 1551-3203
eISSN: 1941-0050


It is our pleasure to present this Special Issue on "Data-Driven Approaches for Complex Industrial Systems" of the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, which provides a forum for researchers and practitioners to report recent results on data-driven methods with applications to complex industrial systems, and to identify critical issues and challenges for future investigations in this field. Roughly, data-driven methods can be categorized into three sets, i.e., data-driven modeling, data-driven monitoring and fault diagnosis, and data-driven control and optimization (cf. Fig. 1). In this Special Issue, 13 papers are selected with novel contributions in data-driven modeling, data-driven monitoring and diagnosis, data-driven control and their industrial applications, respectively.

Last updated on 2020-08-08 at 05:37