A New Trend Heuristic Time-Variant Fuzzy Time Series Method for Forecasting Enrollments
A New Trend Heuristic Time-Variant Fuzzy Time Series Method for Forecasting Enrollments
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 seriesbased 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.
3-540294147
553-564
Sah, Melike
7483d16b-ef9a-4c24-9f00-0a01c630a844
Degtiarev, Konstantin Y.
6e091982-a00d-49f7-84dd-8174fd515778
2005
Sah, Melike
7483d16b-ef9a-4c24-9f00-0a01c630a844
Degtiarev, Konstantin Y.
6e091982-a00d-49f7-84dd-8174fd515778
Sah, Melike and Degtiarev, Konstantin Y.
(2005)
A New Trend Heuristic Time-Variant Fuzzy Time Series Method for Forecasting Enrollments.
International Symposium on Computer and Information Sciences (ISCIS 2005). Lecture Notes In Computer Science.
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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 seriesbased 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.
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Published date: 2005
Venue - Dates:
International Symposium on Computer and Information Sciences (ISCIS 2005). Lecture Notes In Computer Science, 2005-01-01
Organisations:
Electronics & Computer Science
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Local EPrints ID: 265212
URI: http://eprints.soton.ac.uk/id/eprint/265212
ISBN: 3-540294147
PURE UUID: 4e3c8bb3-8d4d-486c-97c7-551b60bed2cb
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Date deposited: 27 Feb 2008 16:52
Last modified: 14 Mar 2024 08:05
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Contributors
Author:
Melike Sah
Author:
Konstantin Y. Degtiarev
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