Title of Paper:Forecasting in time series based on generalized fuzzy logical relationship

Hits:

Date of Publication:2010-10-01

Journal:ICIC Express Letters

Included Journals:EI、Scopus

Volume:4

Issue:5

Page Number:1431-1438

ISSN No.:1881803X

Abstract:Since the fuzzy time series model was proposed in 1993, a number of different extension models have been proposed, which are forecasting with the similar or improved fuzzy logical relationship defined by Song and Chissom. This study presents a new fuzzy logical relationship and an operation for creating fuzzy logical relation matrix to overcome the instability of fuzzy set selection in forecasting process of time series models. Both university enrollment and Shanghai stock index are chosen as the forecasting targets. The empirical results show that the proposed model greatly outperforms the conventional counterparts. ICIC International ? 2010 ISSN.