Masters Theses

Title

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 leaves

Note about bibliography

Includes bibliographical references (leaves 60-62).

Rights

© 2003 Surya Vijay Kanchiraju, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Cluster analysis
Neural networks (Computer science)
Data mining

Thesis Number

T 8423

Print OCLC #

55484158

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

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