eprintid: 8404
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/84/04
datestamp: 2023-11-09 16:20:18
lastmod: 2023-11-09 16:20:18
status_changed: 2023-11-09 16:12:34
type: article
metadata_visibility: show
creators_name: Mansor, R.
creators_name: Othman, M.
creators_name: Kasim, M.M.
title: Fuzzy reasoning based time series forecasting using weighted subsethood model
ispublished: pub
note: cited By 7
abstract: The one central problem in global forecasting area is to minimize the forecasting error and to have a simple model. This paper focuses on the fuzzy time series (FTS) forecasting which is one branch of fuzzy set (FS). Numerous FTS models have been proposed in literature during the past decades and the number of new models is still growing especially in stock markets and student enrolment problems. Some of the FTS models found in literature do not explain the fuzzy logical relationship strength between Ai and Aj which are the lefthand side (LHS) and right-hand side (RHS) of the fuzzy logical relationship respectively. This paper proposed Weighted Subsethood Fuzzy Time Series (WeSuFTS) to build fuzzy reasoning based to address the drawback in forecasting enrolment of students. In this paper, we create the weighted subsethood fuzzy rules to explain the fuzzy relationship between Ai and Aj. The simple centre mid-point defuzzification technique was introduced in defuzzification step. The results show that WeSuFTS method gives promising results where the average error forecasting is 2.31 which is smaller than the one presented by Song and Chissom in 1993 and Chen in 1996, the pioneer of FTS. The proposed method has an advantage since it can give a new interpretation of FTS model. Furthermore, this method able to present the degree of importance of LHS to RHS in explaining the fuzzy logical relationship in FTS. © 2017 American Scientific Publishers. All rights reserved.
date: 2017
publisher: American Scientific Publishers
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032995429&doi=10.1166%2fasl.2017.10030&partnerID=40&md5=e36d52c3a306957b233bf6b8889c60a2
id_number: 10.1166/asl.2017.10030
full_text_status: none
publication: Advanced Science Letters
volume: 23
number: 9
pagerange: 9094-9097
refereed: TRUE
issn: 19366612
citation:   Mansor, R. and Othman, M. and Kasim, M.M.  (2017) Fuzzy reasoning based time series forecasting using weighted subsethood model.  Advanced Science Letters, 23 (9).  pp. 9094-9097.  ISSN 19366612