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Results for Fuzzy time series

Publications & Outputs

  1. A new fuzzy time series method based on an ARMA-type recurrent Pi-Sigma artificial neural network

    Kocak, C., Dalar, A. Z., Yolcu, O. C., Bas, E. & Egrioglu, E., 1/06/2020, In: Soft Computing. 24, 11, p. 8243-8252 10 p.

    Research output: Contribution to journalJournal articlepeer-review

  2. High order fuzzy time series method based on pi-sigma neural network

    Bas, E., Grosan, C., Egrioglu, E. & Yolcu, U., 1/06/2018, In: Engineering Applications of Artificial Intelligence. 72, p. 350-356 7 p.

    Research output: Contribution to journalJournal articlepeer-review

  3. Type-1 fuzzy time series function method based on binary particle swarm optimisation

    Aladag, C. H., Yolcu, U., Egrioglu, E. & Turksen, I. B., 31/01/2016, In: International Journal of Data Analysis Techniques and Strategies. 8, 1, p. 2-13 12 p.

    Research output: Contribution to journalJournal articlepeer-review

  4. Fuzzy-time-series network used to forecast linear and nonlinear time series

    Bas, E., Egrioglu, E., Aladag, C. H. & Yolcu, U., 27/09/2015, In: Applied Intelligence. 43, 2, p. 343-355 13 p.

    Research output: Contribution to journalJournal articlepeer-review

  5. A modified genetic algorithm for forecasting fuzzy time series

    Bas, E., Uslu, V. R., Yolcu, U. & Egrioglu, E., 1/09/2014, In: Applied Intelligence. 41, 2, p. 453-463 11 p.

    Research output: Contribution to journalJournal articlepeer-review

  6. A fuzzy time series approach based on weights determined by the number of recurrences of fuzzy relations

    Rezan Uslu, V., Bas, E., Yolcu, U. & Egrioglu, E., 1/04/2014, In: Swarm and Evolutionary Computation. 15, p. 19-26 8 p.

    Research output: Contribution to journalJournal articlepeer-review

  7. Fuzzy lagged variable selection in fuzzy time series with genetic algorithms

    Aladag, C. H., Yolcu, U., Egrioglu, E. & Bas, E., 1/01/2014, In: Applied Soft Computing Journal. 22, p. 465-473 9 p.

    Research output: Contribution to journalJournal articlepeer-review

  8. PSO-based high order time invariant fuzzy time series method: Application to stock exchange data

    Egrioglu, E., 1/01/2014, In: Economic Modelling. 38, p. 633-639 7 p.

    Research output: Contribution to journalJournal articlepeer-review

  9. Fuzzy time series forecasting with a novel hybrid approach combining fuzzy c-means and neural networks

    Egrioglu, E., Aladag, C. H. & Yolcu, U., 15/02/2013, In: Expert Systems with Applications. 40, 3, p. 854-857 4 p.

    Research output: Contribution to journalJournal articlepeer-review

  10. A new seasonal fuzzy time series method based on the multiplicative neuron model and SARIMA

    Aladag, S., Aladag, C. H., Mentes, T. & Egrioglu, E., 4/12/2012, In: Hacettepe Journal of Mathematics and Statistics. 41, 3, p. 337-345 9 p.

    Research output: Contribution to journalJournal articlepeer-review

  11. A novel seasonal fuzzy time series method

    Alpaslan, F., Cagcag, O., Aladag, C. H., Yolcu, U. & Egrioglu, E., 4/12/2012, In: Hacettepe Journal of Mathematics and Statistics. 41, 3, p. 375-385 11 p.

    Research output: Contribution to journalJournal articlepeer-review

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