A Set of Time Series Prediction Models Based on Difference Method

DOI

10.2991/amms-17.2017.31How to use a DOI?

Keywords

differential rate; a set of time series prediction models; ASD's sum of fraction functions Kj (U, V)

Abstract

This paper proposed a set of time series prediction models based on difference method(ASD). For a time series, the computer can automatically find the time series search method to filter out the ideal in ASD prediction model. For example, the forecast number of registered at the University of Alabama in 1971~1992 years, the ideal forecasting model is Aj (0.000003,0.000003), which can make the mean square error MSE=0 and the average prediction error rate AFER=0%, that thoroughly solve the unsatisfactory prediction accuracy of the existing fuzzy time series forecasting model.

Copyright

© 2017, 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  - Xiaoli Lu
AU  - Hongxu Wang
AU  - Chengguo Yin
AU  - Hao Feng
PY  - 2017/11
DA  - 2017/11
TI  - A Set of Time Series Prediction Models Based on Difference Method
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS 2017)
PB  - Atlantis Press
SP  - 135
EP  - 138
SN  - 1951-6851
UR  - https://doi.org/10.2991/amms-17.2017.31
DO  - 10.2991/amms-17.2017.31
ID  - Lu2017/11
ER  -