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Modelling and Simulation in Engineering
Volume 2011 (2011), Article ID 379121, 5 pages
http://dx.doi.org/10.1155/2011/379121
Research Article

A New Hybrid Methodology for Nonlinear Time Series Forecasting

Department of Industrial Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

Received 7 March 2011; Revised 24 May 2011; Accepted 8 June 2011

Academic Editor: Andrzej Dzielinski

Copyright © 2011 Mehdi Khashei and Mehdi Bijari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [9 citations]

The following is the list of published articles that have cited the current article.

  • Mehdi Khashei, and Mehdi Bijari, “Hybridization of the probabilistic neural networks with feed-forward neural networks for forecasting,” Engineering Applications of Artificial Intelligence, vol. 25, no. 6, pp. 1277–1288, 2012. View at Publisher · View at Google Scholar
  • Simon Fong, Jackie Tai, and Pit Pichappan, “Trend recalling algorithm for automated online trading in stock market,” Journal of Emerging Technologies in Web Intelligence, vol. 4, no. 3, pp. 240–251, 2012. View at Publisher · View at Google Scholar
  • Mehdi Khashei, Farimah Mokhatab Rafiei, and Mehdi Bijari, “Hybrid Fuzzy Auto-Regressive Integrated Moving Average (FARIMAH) Model for Forecasting the Foreign Exchange Markets,” International Journal of Computational Intelligence Systems, vol. 6, no. 5, pp. 954–968, 2013. View at Publisher · View at Google Scholar
  • Lida Barba, Nibaldo Rodríguez, and Cecilia Montt, “Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents,” The Scientific World Journal, vol. 2014, pp. 1–12, 2014. View at Publisher · View at Google Scholar
  • Faycal Rahmoune, Victor Tourtchine, and Kamel Baddari, “Generalized dynamical fuzzy model for identification and prediction,” Journal of Intelligent & Fuzzy Systems, vol. 26, no. 4, pp. 1771–1785, 2014. View at Publisher · View at Google Scholar
  • Minsoo Kim, Yejin Kim, Hyosoo Kim, Wenhua Piao, and Changwon Kim, “Evaluation of the k-nearest neighbor method for forecasting the influent characteristics of wastewater treatment plant,” Frontiers of Environmental Science & Engineering, 2015. View at Publisher · View at Google Scholar
  • Ani Shabri, and Ruhaidah Samsudin, “Fishery Landing Forecasting Using Wavelet-Based Autoregressive Integrated Moving Average Models,” Mathematical Problems in Engineering, vol. 2015, pp. 1–9, 2015. View at Publisher · View at Google Scholar
  • Elpiniki I. Papageorgiou, and Katarzyna Poczȩta, “A Two-Stage Model for Time Series Prediction based on Fuzzy Cognitive Maps and Neural Networks,” Neurocomputing, 2016. View at Publisher · View at Google Scholar
  • Dipankar Mitra, and Ranjit Kumar Paul, “Hybrid time-series models for forecasting agricultural commodity prices,” Model Assisted Statistics and Applications, vol. 12, no. 3, pp. 255–264, 2017. View at Publisher · View at Google Scholar