Learning to Acquire Knowledge in a Smart Grid Environment

被引：0
|
作者：
Liu, Chen-Ching [1 ]
机构：
[1] Washington State Univ, Pullman, WA 99164 USA
来源：
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2015, PT I | 2015年 / 9284卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In a smart grid, a massive amount of data is collected by millions of sensors and meters on the transmission, distribution, and customers' facilities. There is a strong dependence of the smart grid on the information and communications technology for its monitoring and control. As a result, the cyber systems are also an important source of information. This presentation will be focused on the opportunities and challenges for machine learning and knowledge discovery in a smart grid environment. The application areas of (1) anomaly detection for cyber and physical security, and (2) intelligent remedial control of power grids will be used as examples.
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