Masters Theses
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
Subject Headings
Evolutionary computationInvestment analysisMachine learning -- Mathematical modelsTime-series analysis
Thesis Number
T 9377
Print OCLC #
261133506
Electronic OCLC #
226378581
Recommended Citation
Gore, Christopher Mark, "A time series classifier" (2008). Masters Theses. 4609.
https://scholarsmine.mst.edu/masters_theses/4609