Guest Editorial Big Data Analytics: Risk and Operations Management for Industrial Applications

被引：13

作者：

Chan, Hing Kai ^{[1
]}

Choi, Tsan-Ming ^{[2
]}

Yue, Xiaohang ^{[3
]}

机构：

[1] Univ Nottingham Ningbo, Nottingham Univ Business Sch China, Ningbo, Zhejiang, Peoples R China

[2] Hong Kong Polytech Univ, Kowloon, Hong Kong, Peoples R China

[3] Univ Wisconsin, Milwaukee, WI 53201 USA

来源：

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS | 2016年 / 12卷 / 03期

关键词：

Big data;

D O I：

10.1109/TII.2016.2558477

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The special section of IEEE Transactions On Industrial Informatics focuses more on the handling and analysis of the collected data. It is expected that analyzing the data can improve the reliability of industrial systems by predicting the occurrence of potential risks and then rectification can be made accordingly. These risks are linked to uncertain factors hidden in the systems that can be revealed by the data analysis process. The operations of the whole industrial system follow certain logic based on the sensory network in the system.

引用

页码：1214 / 1218

页数：5

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