Fuzzy time series forecasting model based on second order fuzzy logical relationship and similarity measure / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli

Nik Badrul Alam, Nik Muhammad Farhan Hakim and Ramli, Nazirah (2019) Fuzzy time series forecasting model based on second order fuzzy logical relationship and similarity measure / Nik Muhammad Farhan Hakim Nik Badrul Alam and Nazirah Ramli. Multidisciplinary Informatics Journal, 2 (2). pp. 117-125. ISSN 2637-0042

Abstract

Various fuzzy time series (FTS) forecasting methods have been proposed to cater for data in linguistic values. In this paper, an improved FTS forecasting method based on second order fuzzy logical relationship is proposed and it is used to forecast the enrollment of students in the University of Alabama. The performance of the forecasted results is compared to the actual data by using seven different similarity measures. The hybrid similarity measure based on geometric distance, centre of gravity, area, perimeter and height gives the best performance.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Nik Badrul Alam, Nik Muhammad Farhan Hakim
farhanhakim@uitm.edu.my
Ramli, Nazirah
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities > Data processing
Q Science > QA Mathematics > Fuzzy logic
Divisions: Universiti Teknologi MARA, Perak > Tapah Campus > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Multidisciplinary Informatics Journal
UiTM Journal Collections: Others > Multidisciplinary Informatics Journal - DISCONTINUE
ISSN: 2637-0042
Volume: 2
Number: 2
Page Range: pp. 117-125
Keywords: Fuzzy Time Series; Similarity Measure; Second Order; Trapezoidal Fuzzy Number
Date: December 2019
URI: https://ir.uitm.edu.my/id/eprint/39324
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