Application of data mining algorithms for anomaly detection in intra transport facility
"In this research, two data mining methods, clustering and neural network classifications are investigated for the detection of anomalies. Clustering is a technique where similar data points are grouped tegether to obtain patterns that have to be analyzed to detect anomalies. Neural network classification deals with separating data points as normal or anomalous. Results obtained from clustering helped in the detection of some driving patterns while the neural networks detected the anomalies in a better fashion than clustering."--Abstract, page iii.
M.S. in Computer Science
University of Missouri--Rolla
xii, 88 leaves
© 2003 Surya Vijay Kanchiraju, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Neural networks (Computer science)
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5090220~S5
Kanchiraju, Surya Vijay, "Application of data mining algorithms for anomaly detection in intra transport facility" (2003). Masters Theses. 2462.
This document is currently not available here.