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Fourier Transform Based Spatial Outlier Mining.

Authors :
Rasheed, Faraz
Peng, Peter
Alhajj, Reda
Rokne, Jon
Source :
Intelligent Data Engineering & Automated Learning - Ideal 2009; 2009, p317-324, 8p
Publication Year :
2009

Abstract

Outlier detection is an important problem in spatial analysis which involves finding a region of spatial locations with features significantly different from the rest of the population. In this paper, we used fast fourier transform to highlight the areas with high frequency change. The spatial points identified by the fourier transform are then reconfirmed with Z-value test and outlier regions are identified. We performed several experiments to highlight the accuracy and efficiency of the approach and compared it with some other existing approaches. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783642043932
Database :
Complementary Index
Journal :
Intelligent Data Engineering & Automated Learning - Ideal 2009
Publication Type :
Book
Accession number :
76843040
Full Text :
https://doi.org/10.1007/978-3-642-04394-9_39