Title
QSSI: A NEW SIMILARITY INDEX FOR QUALITATIVE TIME SERIES. APPLICATION TO CLASSIFY VOLTAGE SAGS
Abstract
This work is focused on defining and implementing a new similarity criterion for sequences of symbolic representations. The proposed algorithm returns a normalized index related to the degree of matching between sequences of qualitative labels. Performance of this method has been tested in the classification of voltage sags (transient reduction of voltage magnitude) gathered at 25 kV distribution substations. The objective is to assist monitoring systems in locating the origin of such disturbances in the transmission (HV) or distribution (MV) system. The promising classification accuracy achieved when this method was used with test data suggests that the presented algorithm could be applied satisfactorily and confirms its utility in classification approaches.
Year
DOI
Venue
2011
10.1080/08839514.2011.545213
Applied Artificial Intelligence
Keywords
Field
DocType
promising classification accuracy,normalized index,qualitative label,voltage magnitude,proposed algorithm,classification approach,classify voltage sags,qualitative time series,symbolic representation,kv distribution substation,new similarity index,voltage sag,new similarity criterion,indexation,time series
Data mining,Magnitude (mathematics),Normalization (statistics),Monitoring system,Pattern recognition,Computer science,Voltage,Similarity criterion,Test data,Artificial intelligence,Machine learning
Journal
Volume
Issue
ISSN
25
2
0883-9514
Citations 
PageRank 
References 
3
0.39
12
Authors
3
Name
Order
Citations
PageRank
Francisco Gamero181.54
Joaquim Melendez272.97
Joan Colomer3135.21