ACADSTAFF UGM

CREATION
Title : Automatic time series forecasting using nonlinear autoregressive neural network model with exogenous input
Author :

HERMANSAH (1) Prof. Dr.rer.nat. Dedi Rosadi, S.Si., M.Sc. (2) Dr. Abdurakhman (3) Dr. Herni Utami, S.Si., M.Si. (4)
Date : 5 2021
Keyword : Automatic forecasting Ensemble operator NARX model Neural network Stepwise algorithm Time series Automatic forecasting Ensemble operator NARX model Neural network Stepwise algorithm Time series
Abstract : This study aims to determine an automatic forecasting method of univariate time se- ries, using the nonlinear autoregressive neural network model with exogenous input (NARX). In this automatic setting, users only need to supply the input of time series. Then, an automatic forecasting algorithm sets up the appropriate features, estimate the parameters in the model, and calculate forecasts, without the users’ intervention. The algorithm method used include preprocessing, tests for trends, and the application of first differences. The time series were tested for seasonality, and seasonal differences were obtained from a successful analysis. These series were also linearly scaled to [−1, +1]. The autoregressive lags and hidden neurons were further selected through the stepwise and optimization algorithms, respectively. The 20 NARX models were fitted with different random starting weights, and the forecasts were combined using the ensemble operator, in order to obtain the final product. This proposed method was applied to real data, and its performance was compared with several available auto- matic models in the literature. The forecasting accuracy was also measured by mean squared error (MSE) and mean absolute percent error (MAPE), and the results showed that the proposed method outperformed the other automatic models.
Group of Knowledge : Statistik
Original Language : English
Level : Internasional
Status :
Published
Document
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1 BEEI Hermansah automatic ts forecasting.pdf
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2 Similarity Automatic time series forecasting using nonlinear autoregressive neural network model with exogenous input.pdf
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3 2021 memen beei paper.pdf
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