Masters Theses
Application of data mining algorithms for anomaly detection in intra transport facility
Abstract
"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.
Department(s)
Computer Science
Degree Name
M.S. in Computer Science
Publisher
University of Missouri--Rolla
Publication Date
Fall 2003
Pagination
xii, 88 pages
Rights
© 2003 Surya Vijay Kanchiraju, All rights reserved.
Document Type
Thesis - Citation
File Type
text
Language
English
Subject Headings
Cluster analysisNeural networks (Computer science)Data mining
Thesis Number
T 8423
Print OCLC #
55484158
Recommended Citation
Kanchiraju, Surya Vijay, "Application of data mining algorithms for anomaly detection in intra transport facility" (2003). Masters Theses. 2462.
https://scholarsmine.mst.edu/masters_theses/2462
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