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

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 t...

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Main Authors: Ramli, Nazirah, Md. Tap, Abu Osman
Format: Article
Language:English
Published: Universiti Teknologi MARA Cawangan Pahang 2009
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/33605/
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author Ramli, Nazirah
Md. Tap, Abu Osman
author_facet Ramli, Nazirah
Md. Tap, Abu Osman
author_sort Ramli, Nazirah
building UiTM Institutional Repository
collection Online Access
description 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.
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spelling uitm-336052022-09-23T08:53:26Z https://ir.uitm.edu.my/id/eprint/33605/ 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 Ramli, Nazirah Md. Tap, Abu Osman Fuzzy arithmetic Problems, exercises, etc. Temperature 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. Universiti Teknologi MARA Cawangan Pahang 2009 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/33605/1/33605.PDF 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. (2009) Gading Business and Management Journal <https://ir.uitm.edu.my/view/publication/Gading_Business_and_Management_Journal.html>, 13 (01). pp. 1-14. ISSN 0128-5599
spellingShingle Fuzzy arithmetic
Problems, exercises, etc.
Temperature
Ramli, Nazirah
Md. Tap, Abu Osman
Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title_full Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title_fullStr Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title_full_unstemmed Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title_short Forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / Nazirah Ramli and Abu Osman Md. Tap
title_sort forecasting students' enrolment in fuzzy time series based on three classes of t-norm of subsethood defuzzification / nazirah ramli and abu osman md. tap
topic Fuzzy arithmetic
Problems, exercises, etc.
Temperature
url https://ir.uitm.edu.my/id/eprint/33605/