By Topic

Patterns and Outlier Analysis of Traffic Flow Using Data Signatures via IDIRBrG Method and Vector Fusion Visualization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

11 Author(s)
Malinao, J.A. ; Dept. of Comput. Sci., Univ. of the Philippines, Quezon City, Philippines ; Juayong, R.A.B. ; Becerral, J.G. ; Cabreros, K.R.C.
more authors

In this paper, we used X-Means clustering algorithm, incorporated data images from a so-called Iterative Data Image Rotated Bar Graph (iDIRBrG) method (formerly referred as BC method) and used Vector Fusion Visualization to achieve better traffic data analysis results compared to our previous work by improving how data signatures are constructed from the raw data set. By doing so, we effectively identify more patterns, extracted known as well as unexpected outliers, and novel information from the data set. These results were validated by experts from the NCTS. Furthermore, we also show more simplistic frequency-domain 2D visualizations of the entire data set. These successfully expose the internal structure and relationship of each individual point as well as the clusters obtained from it. Hence, using the methods above, we provide an effective and efficient time series traffic analysis.

Published in:

Human-Centric Computing (HumanCom), 2010 3rd International Conference on

Date of Conference:

11-13 Aug. 2010