Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap

Ramli, Nazirah and Md. Tap, Abu Osman (2009) Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap. Gading Business and Management Journal, 13 (01). pp. 1-14. ISSN 0128-5599

Abstract

Traditional time series methods can predict the seasonal problem but fail to forecast the problems with linguistic values. An improvised forecasting method by using fuzzy time series can be applied to deal with this problems. This paper presents three classes oft-norm of subsethood defuzzification that are algebraic product, Einstein product and minimum inforecasting the students' enrolments based on fuzzy time series. The proposed method uses the historical data of students' enrolment and applies seven and ten intervals with equal length and the max-product and max-min as the composition operator in the fuzzy relations. The result shows that the t-norm of algebraic product class of subsethood defuzzijication model with (10, max-product) is the best forecasting methods in terms of accuracy. The t-norm of algebraic product class with (I 0, max-product) also achieves higher forecasting accuracy rates compared to some of the existing methods.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ramli, Nazirah
nazirahr@pahang.uitm.edu.my
Md. Tap, Abu Osman
abuosman@kict.iiu.edu.my
Subjects: Q Science > QA Mathematics > Fuzzy arithmetic
Q Science > QA Mathematics > Problems, exercises, etc.
Q Science > QC Physics > Heat > Temperature
Divisions: Universiti Teknologi MARA, Pahang > Jengka Campus
Journal or Publication Title: Gading Business and Management Journal
UiTM Journal Collections: Others > GADING
ISSN: 0128-5599
Volume: 13
Number: 01
Page Range: pp. 1-14
Keywords: Forecasting enrolments, max-min composition, max-product composition, subsethood defuzzification, t-norm classes
Date: 2009
URI: https://ir.uitm.edu.my/id/eprint/33605
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