Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli

Fuzzy time series(FTS) is a well-known method for forecasting the time series data in linguistic values. Recently, a few studies have used the similarity measure approach in determining the performance of the FTS forecasting model. In this paper, an FTS forecasting model based on seven int...

Full description

Bibliographic Details
Main Authors: Nik Badrul Alam, Nik Muhammad Farhan Hakim, Ramli, Nazirah
Format: Article
Language:English
Published: Universiti Teknologi MARA Cawangan Pahang 2019
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/31176/
_version_ 1848807688394244096
author Nik Badrul Alam, Nik Muhammad Farhan Hakim
Ramli, Nazirah
author_facet Nik Badrul Alam, Nik Muhammad Farhan Hakim
Ramli, Nazirah
author_sort Nik Badrul Alam, Nik Muhammad Farhan Hakim
building UiTM Institutional Repository
collection Online Access
description Fuzzy time series(FTS) is a well-known method for forecasting the time series data in linguistic values. Recently, a few studies have used the similarity measure approach in determining the performance of the FTS forecasting model. In this paper, an FTS forecasting model based on seven intervals of equal length and trapezoidal fuzzy numbers is presented. Then, the performance of FTS forecasting model using various types of similarity measure is compared. The FTS model is implemented in the case of students’ enrollment in the University of Alabama and the unemployment rate in Malaysia. The hybrid similarity measure of geometric distance, center of gravity, area, perimeter and height gives the best performance
first_indexed 2025-11-14T22:46:48Z
format Article
id uitm-31176
institution Universiti Teknologi MARA
institution_category Local University
language English
last_indexed 2025-11-14T22:46:48Z
publishDate 2019
publisher Universiti Teknologi MARA Cawangan Pahang
recordtype eprints
repository_type Digital Repository
spelling uitm-311762022-09-23T08:50:29Z https://ir.uitm.edu.my/id/eprint/31176/ Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli gadingst Nik Badrul Alam, Nik Muhammad Farhan Hakim Ramli, Nazirah Research QA Mathematics T Technology (General) Fuzzy time series(FTS) is a well-known method for forecasting the time series data in linguistic values. Recently, a few studies have used the similarity measure approach in determining the performance of the FTS forecasting model. In this paper, an FTS forecasting model based on seven intervals of equal length and trapezoidal fuzzy numbers is presented. Then, the performance of FTS forecasting model using various types of similarity measure is compared. The FTS model is implemented in the case of students’ enrollment in the University of Alabama and the unemployment rate in Malaysia. The hybrid similarity measure of geometric distance, center of gravity, area, perimeter and height gives the best performance Universiti Teknologi MARA Cawangan Pahang 2019 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/31176/1/31176.pdf Nik Badrul Alam, Nik Muhammad Farhan Hakim and Ramli, Nazirah (2019) Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli. (2019) Gading Journal for Science and Technology <https://ir.uitm.edu.my/view/publication/Gading_Journal_for_Science_and_Technology.html>, 2 (2). pp. 17-25. ISSN 2637-0018
spellingShingle Research
QA Mathematics
T Technology (General)
Nik Badrul Alam, Nik Muhammad Farhan Hakim
Ramli, Nazirah
Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title_full Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title_fullStr Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title_full_unstemmed Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title_short Fuzzy time series forecasting model based on various types of similarity measure approach / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli
title_sort fuzzy time series forecasting model based on various types of similarity measure approach / nik muhammad farhan hakim nik badrul alam and nazirah ramli
topic Research
QA Mathematics
T Technology (General)
url https://ir.uitm.edu.my/id/eprint/31176/