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Title

A Comparative Study of Seasonal Interval Models for Industrial Time Series Forecasting

Year: 1391
COI: IIEC09_186
Language: EnglishView: 1,266
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Authors

Mehdi Khashei - Isfahan University of Technology
Farimah Mokhatab Rafiei - Isfahan University of Technology
Akram Mir Ahmadi - Isfahan University of Technology

Abstract:

In recent years, various seasonal time series models have been proposed for industrial and financial markets forecasting. In each case, the accuracy of time series forecastingare fundamental to make decision and hence the research for improving the effectiveness of seasonal forecasting models havebeen curried on. Many researchers have compared different seasonal time series models together in order to determine moreefficient once in industrial and financial markets. In this paper, performance of four seasonal interval time series models including seasonal autoregressive integrated moving average (SARIMA), fuzzy seasonal autoregressive integrated moving average (FSARIMA), fuzzy seasonal multi-layer perceptron(FSMLP), and Watada models are compared together. Empirical results indicate that the FSMLP model is more satisfactory thanother those models. Therefore, it can be a suitable alternativemodel for seasonal interval forecasting of industrial and financial time series.

Keywords:

Seasonal interval forecasting , Multi-Layer perceptrons (MLPs) , Seasonal Auto-Regressive Integrated Moving Average (SARIMA) , Fuzzy logic and Fuzzy models , Industrial and financial time series

Paper COI Code

This Paper COI Code is IIEC09_186. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/189065/

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Khashei, Mehdi and Mokhatab Rafiei, Farimah and Mir Ahmadi, Akram,1391,A Comparative Study of Seasonal Interval Models for Industrial Time Series Forecasting,9th International Industrial Engineering Conference,Tehran,https://civilica.com/doc/189065

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Type of center: دانشگاه دولتی
Paper count: 14,177
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