A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
The Set of Improved Fuzzy Time Series Forecasting Models Based on the Ordered Difference Rate
2017
Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017)
unpublished
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
doi:10.2991/msam-17.2017.10
fatcat:6rle3l2ncffsjafzxvn5nx4cnm