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Book Chapter
A New Trend Heuristic Time-Variant Fuzzy Time Series Method for Forecasting Enrollments
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 3733/2005
Book
Computer and Information Sciences - ISCIS 2005
DOI
10.1007/11569596
Copyright
2005
ISBN
978-3-540-29414-6
Category
Information Retrieval and Natural Language
DOI
10.1007/11569596_58
Pages
553-564
Subject Collection
Computer Science
SpringerLink Date
Wednesday, November 16, 2005
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Information Retrieval and Natural Language
A New Trend Heuristic Time-Variant Fuzzy Time Series Method for Forecasting Enrollments
Melike Şah
1
and Konstantin Degtiarev
1
(1)
Computer Engineering Department, Eastern Mediterranean University, Mersin 10, PO Box-95, Turkey
Abstract
In this paper, we have proposed a new modified forecasting method based on time-variant fuzzy time series. It uses trend heuristics in addition to high-order fuzzy logical relations and enhances the average forecasting accuracy significantly. To illustrate the whole forecasting process, we use actual enrollments (historical data for 22 years) of the University of Alabama (UA) and compare results obtained through other well-known fuzzy time series-based approaches described up to date in the literature. As a result, for all examined cases, the new time-variant method yields better forecasting accuracy as compared with alternative methods.
Melike
Şah
Email:
melike.sah@emu.edu.tr
Konstantin
Degtiarev
Email:
konstantin.degtiarev@emu.edu.tr
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