DocumentCode
3066512
Title
Notice of Retraction
Design data structure for WAMS datastream mining base on GPS time scale
Author
Yunqi Kan ; Zhaoyang Qu
Author_Institution
Northeast Dianli Univ., Jilin, China
fYear
2010
fDate
18-19 Oct. 2010
Firstpage
1
Lastpage
3
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
WAMS application platform to power dynamic real-time monitoring possible, the amount of data generated by WAMS platform very large, and the datastream flow to the control center in High-speed. It is a problem need to Resolved that How to use the WAMS data to judge abnormalities of power system rapidly. For mining in WAMS data stream, this paper explore the model of data stream and elements used to identify disturbance type. This paper explores the datastream model and identify the elements of disturbance, and propose summary of a data stream mining data structure against the feature of power system. It provides an important basis for for further research on data stream mining algorithms.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
WAMS application platform to power dynamic real-time monitoring possible, the amount of data generated by WAMS platform very large, and the datastream flow to the control center in High-speed. It is a problem need to Resolved that How to use the WAMS data to judge abnormalities of power system rapidly. For mining in WAMS data stream, this paper explore the model of data stream and elements used to identify disturbance type. This paper explores the datastream model and identify the elements of disturbance, and propose summary of a data stream mining data structure against the feature of power system. It provides an important basis for for further research on data stream mining algorithms.
Keywords
Global Positioning System; data mining; data structures; power engineering computing; power system measurement; GPS time scale; WAMS datastream mining; datastream flow; design data structure; power dynamic real-time monitoring; power system; Data mining; Data models; Data structures; Histograms; Monitoring; Power system dynamics; GPS time scale; WAMS; datastream mining; histogram;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Congress (GMC), 2010 Global
Conference_Location
Shanghai
Print_ISBN
978-1-4244-9001-1
Type
conf
DOI
10.1109/GMC.2010.5634582
Filename
5634582
Link To Document