Comparing of ARIMA and RBFNN for short-term forecasting

(1) * Haviluddin Haviluddin Mail (Universitas Mulawarman, Indonesia)
(2) Ahmad Jawahir Mail (Researcher at ICT of Mulawarman University, Indonesia)
*corresponding author

Abstract


Based on a combination of an autoregressive integrated moving average (ARIMA) and a radial basis function neural network (RBFNN), a time-series forecasting model is proposed. The proposed model has examined using simulated time series data of tourist arrival to Indonesia recently published by BPS Indonesia. The results demonstrate that the proposed RBFNN is more competent in modelling and forecasting time series than an ARIMA model which is indicated by mean square error (MSE) values. Based on the results obtained, RBFNN model is recommended as an alternative to existing method because it has a simple structure and can produce reasonable forecasts.

Keywords


ARIMA; RBFNN; MSE; Tourist arrival

   

DOI

https://doi.org/10.26555/ijain.v1i1.10
      

Article metrics

Abstract views : 1275 | PDF views : 477

   

Cite

   

Full Text

Download

References


G. Chen, K. Fu, Z. Liang, T. Sema, C. Li, P. Tontiwachwuthikul, and R. Idem, "The genetic algorithm based back propagation neural network for MMP prediction in CO2-EOR process," Fuel, vol. 126, pp. 202–212, 2014.

Haviluddin and R. Alfred, "Forecasting Network Activities Using ARIMA Method," Journal of Advances in Computer Networks, vol. 2, pp. 173-179, 2014.

N. M. Yusof, R. S. A. Rashid, and Z. Mohamed, "Malaysia Crude Oil Production Estimation: an Application of ARIMA Model," in 2010 International Conference on Science and Social Research (CSSR 2010), Kuala Lumpur, Malaysia, 2010.

M. Valipour, M. E. Banihabib, and S. M. R. Behbahani, "Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir," Journal of Hydrology, vol. 476, pp. 433–441, 2013.

Haviluddin and R. Alfred, "Daily Network Traffic Prediction Based on Backpropagation Neural Network," Australian Journal of Basic and Applied Sciences, vol. 8(24), pp. 164-169, 2014.

Haviluddin, A. Sunarto, and S. Yuniarti, "A Comparison between Simple Linear Regression and Radial Basis Function Neural Network (RBFNN) Models for Predicting Students’ Achievement.," in International Conference on Education 2014 (ICEdu14) 4th - 6th June 2014., Universiti Malaysia Sabah - Kota Kinabalu, Malaysia, 2014, pp. 99-308.

Y. Perwej and A. Perwej, "Prediction of the Bombay Stock Exchange (BSE) Market Returns Using Artificial Neural Network and Genetic Algorithm," Journal of Intelligent Learning Systems and Applications, vol. 4, pp. 108-119, 2012.

L. Yizhen, Z. Wenhua, l. Lin, j. Wu, and L. Gang, "The forecasting of Shanghai Index trend Based on Genetic Algorithm and Back Propagation Artificial Neural Network Algorithm," in The 6th International Conference on Computer Science & Education (ICCSE 2011), SuperStar Virgo, Singapore, 2011.

K. Abhishek, A. Kumar, R. Ranjan, and S. Kumar, "A Rainfall Prediction Model using Artificial Neural Network," 2012 IEEE Control and System Graduate Research Colloquium (ICSGRC 2012), 2012.

M. Majumder and R. N. Barman, "Application of Artificial Neural Networks in Short-Term Rainfall Forecasting," Application of Nature Based Algorithm in Natural Resource Management, 2013.

J. Wu, J. Long, and M. Liu, "Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm," Neurocomputing, vol. 148, pp. 136–142, 2015.

J. W. Yu, "Rainfall time series forecasting based on Modular RBF Neural Network model coupled with SSA and PLS," Journal of Theoretical and Applied Computer Science, vol. 6, pp. 3-12, 2012.

G. E. P. Box, G. M. Jenskins, and G. C. Reinsel. (2008). Time Series Analysis Forecasting and Control 4th Edition.




Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

___________________________________________________________
International Journal of Advances in Intelligent Informatics
ISSN 2442-6571  (print) | 2548-3161 (online)
Organized by Informatics Department - Universitas Ahmad Dahlan , and UTM Big Data Centre - Universiti Teknologi Malaysia
Published by Universitas Ahmad Dahlan
W : http://ijain.org
E : info@ijain.org, andri.pranolo@tif.uad.ac.id (paper handling issues)
     ijain@uad.ac.id, andri.pranolo.id@ieee.org (publication issues)

View IJAIN Stats

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0