Fuzzy Time Series Forecasting Model of Inverse Fuzzy Number Based on Percentage Year by Year of Continuous Point

DOI

10.2991/icemc-16.2016.58How to use a DOI?

Keywords

Percentage; Continuous point; Inverse fuzzy number; Fuzzy time-series forecasting

Abstract

Fuzzy time-series forecasting model of inverse fuzzy number based on percentage year to year of continuous point is proposed. We improved the forecasting model of Saxena. The new model puts the percentage year to year of historical data as for the domain of discourse, uses percentage year to year of continuous point to define fuzzy number, and then defines the corresponding inverse fuzzy number. At last we again provide the predictor formula and study the prediction problem of freshman registration number at the University of Alabama, in order to demonstrate the application of a new prediction model. The results show that AFER and MSE of the model are very small compared with the existing models.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haifeng Wang
AU  - Kun Zhang
AU  - Zhuang Li
AU  - Hongxu Wang
PY  - 2016/05
DA  - 2016/05
TI  - Fuzzy Time Series Forecasting Model of Inverse Fuzzy Number Based on Percentage Year by Year of Continuous Point
BT  - Proceedings of the 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SP  - 279
EP  - 284
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.58
DO  - 10.2991/icemc-16.2016.58
ID  - Wang2016/05
ER  -