The Set of Improved Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate

被引：0

作者：

Yin, Chengguo ^{[1
]}

Wang, Hongxu ^{[2
]}

Feng, Hao ^{[3
]}

Lu, Xiaoli ^{[2
]}

机构：

[1] Hainan Trop Ocean Univ, Sch Ocean Informat Engn, Sanya 572022, Hainan, Peoples R China

[2] Hainan Trop Ocean Univ, Sch Ocean Business, Sanya 572022, Hainan, Peoples R China

[3] Hainan Trop Ocean Univ, Sch Ocean Sci & Technol, Sanya 572022, Hainan, Peoples R China

来源：

PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MODELLING, SIMULATION AND APPLIED MATHEMATICS (MSAM2017) | 2017年 / 132卷

关键词：

fuzzy time series forecasting method; fuzzy number function of SIFBODR; inverse fuzzy number function of SIFBODR; forecasting function of SIFBODR; ENROLLMENTS;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Song and Chissom first proposed the fuzzy time series forecasting model in 1993. In this paper, we improved the forecasting model proposed by Stevenson and Porter, and dug out the SIFBODR (The Set of Improved Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate). In the research on the forecasting problem of enrollments of the University of Alabama 1971-1992, the forecasting model SIFBODR(0.00002, 0.00004) of SIFBODR can obtain AFER (Average Forecasting Error Rate) = 0% and MSE(Mean Square Error) = 0. The problem that the prediction accuracy of fuzzy time series forecasting models is not high for many years is basically solved.

引用

页码：38 / 41

页数：4

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