Abstract

"A time series is a sequence of data measured at successive time intervals. Time series analysis refers to all of the methods employed to understand such data, either with the purpose of explaining the underlying system producing the data or to try to predict future data points in the time series...An evolutionary algorithm is a non-deterministic method of searching a solution space, and modeled after biological evolutionary processes. A learning classifier system (LCS) is a form of evolutionary algorithm that operates on a population of mapping rules. We introduce the time series classifier TSC, a new type of LCS that allows for the modeling and prediction of time series data, derived from Wilson's XCSR, an LCS designed for use with real-valued inputs. Our method works by modifying the makeup of the rules in the LCS so that they are suitable for use on a time series...We tested TSC on real-world historical stock data"--Abstract, page iii.

Advisor(s)

Tauritz, Daniel R.

Committee Member(s)

Luechtefeld, Ray
Wilkerson, Ralph W.

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2008

Pagination

ix, 56 pages

Note about bibliography

Includes bibliographical references (pages 152-159) and appendixes.

Rights

© 2008 Christopher Mark Gore, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Evolutionary computation
Investment analysis
Machine learning -- Mathematical models
Time-series analysis

Thesis Number

T 9377

Print OCLC #

261133506

Electronic OCLC #

226378581

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