Publications

These publications, authored by Assoc. Prof. Dr. Nihat Tak, focus on advanced approaches in fuzzy logic, recurrent modeling, and possibilistic frameworks, aiming to enhance feature selection, clustering, and predictive performance in complex data environments

  • Tak, N.,&Uçan, A. (2026), Meta fuzzy feature-selection-based regression functions. Applied Soft Computing,190,114592.
  • Tak, A. Y., & Tak, N. (2026). Type-1 fuzzy functions for forecasting: A literature review and bibliometric analysis. Fuzzy Sets and Systems, 527, 109697.
  • Ataş, P. K., Tak, N., Özöğür-Akyüz, S., & Erdogan, B. E. (2025). An Innovative Approach to Ensemble Learning in Bankruptcy Prediction using Support Vector Machines and Meta Fuzzy Functions. Information Sciences, 122450.
  • Yabacı Tak, A., Tak, N., Ilgen Uslu, F., & Yucesan, E. (2024). Diagnostic Panel of Three Genetic Biomarkers Based on Artificial Neural Network for Patients With Idiopathic Generalized Epilepsy. Acta Neurologica Scandinavica, 2024(1), 8853018.
  • Cevik, F. C., Gever, B., Tak, N., & Khaniyev, T. (2023). Forecast combination approach with meta-fuzzy functions for forecasting the number of immigrants within the maritime line security project in Turkey. Soft Computing, 27(5), 2509-2535.
  • Gök, A., & Tak, N. (2023). Dating currency crisis and assessing the determinants based on meta fuzzy index functions. Computational Economics, 61(3), 1225-1250.
  • Tak, N., & Gök, A. (2022). Dating currency crises and designing early warning systems: Meta‐possibilistic fuzzy index functions. International Journal of Finance & Economics, 27(3), 3773-3790.
  • Tak, N. (2022). A novel ARMA type possibilistic fuzzy forecasting functions based on grey-wolf optimizer (ARMA-PFFs). Computational Economics, 59(4), 1539-1556.
  • Tak, N., & İnan, D. (2022). Type-1 fuzzy forecasting functions with elastic net regularization. Expert Systems with Applications, 199, 116916.
  • Tak, N. (2021). Forecast combination with meta possibilistic fuzzy functions. Information Sciences, 560, 168-182.
  • Tak, N. (2021). Meta fuzzy functions based feed-forward neural networks with a single hidden layer for forecasting. Journal of Statistical Computation and Simulation, 91(13), 2800-2816.
  • Tak, N., Egrioglu, E., Bas, E., & Yolcu, U. (2021). An adaptive forecast combination approach based on meta intuitionistic fuzzy functions. Journal of Intelligent & Fuzzy Systems, 40(5), 9567-9581.
  • Tak, N. (2020). Type-1 recurrent intuitionistic fuzzy functions for forecasting. Expert systems with applications, 140, 112913.
  • Tak, N. (2020). Type-1 possibilistic fuzzy forecasting functions. Journal of Computational and Applied Mathematics, 370, 112653.
  • Tak, N. (2018). Meta fuzzy functions: Application of recurrent type-1 fuzzy functions. Applied Soft Computing, 73, 1-13.
  • Tak, N., Evren, A. A., Tez, M., & Egrioglu, E. (2018). Recurrent type-1 fuzzy functions approach for time series forecasting. Applied Intelligence, 48(1), 68-77.
  • N. TAK, A. UÇAN & D. YILDIZ, Type-1 Fuzzy Lasso Regression Functions, Sözlü Sunum, The 19th International Days of Statistics and Economics, 04 September 2025, 05 September 2025, 367 – 376.
  • N. TAK, Possibilistic Fuzzy Functions for forecasting Stock Exchange Indices, Sözlü Sunum, The 18th International Days of Statistics and Economics, 05 September 2024, 06 September 2024.
  • A. YILDIZ & N. TAK, Bulanık Kümeleme Yöntemleri Yapay Zekâ Uygulamalarında Neden Önemli?, Sözlü Sunum, V. INTERNATIONAL APPLIED STATISTICS CONGRESS (UYIK – 2024), 21 May 2024, 23 May 2024.
  • A. UÇAN, D. YILDIZ & N. TAK, Performance Comparison of Classification Algorithms Using Feature Selection Methods in Machine Learning, Sözlü Sunum, Uluslararası Uygulamalı Istatistik Konfresi, 21 May 2024, 23 May 2024.
  • B. GEVER EKINCI, F. Ç. ÇEVIK, N. TAK & T. KHANIYEV, Forecasting of number of international immigrants in Turkey’s sea lane, S.zlü Sunum, The 22nd Conference of the International Federation of Operational Research Societies (IFORS21), 23 August 2021, 27 August 2021.
  • N. TAK & D. INAN, Type-1 Panelized Regression Functions, Sözlü Sunum, 11TH International Statistics Congress, 04 October 2019, 08 October 2019.
  • N. TAK, E. EGRIOGLU, U. YOLCU & E. BAS, Combination of Forecasting Methods based on Fuzzy C-Means Clustering, Sözlü Sunum, 11. International Statistics Days Conference, 03 October 2018, 07 October 2018.
  • N. TAK, Meta Fuzzy Currency Crisis Index Functions, Sözlü Sunum, InternationalConference on Trends and Perspectives in Linear Statistical Inference, LinStat 2018, 20 August 2018, 24 August 2018.
  • N. TAK & E. C. YALÇIN, Bulanık C- Ortalamalar Metodu Ile Süre. Yetenek Indekslerine Yönelik Bir Çalısma, Sözlü Sunum, XVIII. Uluslararası Ekonometri, Yöneylem Arastırması ve Istatistik Sempozyumu, 05 October 2017, 07 October 2017.
  • N. TAK & E. C. YALÇIN, Zaman Serileri Öngörülerinde Boz-Kurt Optimizasyon Temelli Geri Beslemeli Bulanık Fonksiyon Yaklasımı, S.zlü Sunum, XVIII. Uluslararası Ekonometri, Yöneylem Arastırması ve Istatistik Sempozyumu, 05 October 2017, 07 October 2017.
  • N. TAK, E. ÇEVIK & E. C. YALÇIN, Gü.lü Ekonomiye Geçis Döneminde Turizme Dayalı Büyümenin Öngörü Performansının Karsılastırmalı Analizi, Sözlü Sunum, I. Uluslararası Ekonomi, Finans ve Ekonometri Sempozyumu, 21 September 2017, 23 September 2017.
  • N. TAK, Recurrent Fuzzy Functions Approach Based on Grey Wolf Optimizer for Time Series Forecasting, Sözlü Sunum, 3rd International Researchers, Statisticians and Young Statisticians Congress 2017, 24 May 2017, 26 May 2017.
  • N. TAK, A. A. EVREN, M. TEZ & E. EGRIOGLU, Recurrent Type-1 Fuzzy Regression Function for Time Series Forecasting, S.zlü Sunum, International Conference on Trends and Perspectives in Linear Statistical Inference, 22 -25 August 2016.
  • N. TAK, Type 1 Fuzzy Function Approach for Time Series Forecasting, Sözlü Sunum, XVIII. Uluslararası Ekonometri, Yöneylem Arastırması ve Istatistik Sempozyumu, 07 May 2015, 12 May 2015.
  • N. TAK, Meta Bulanık Fonksiyonlar, İstatistikte Güncel Konular-III(61 – 75), ISBN: 978-625-385-272-6: Egitim Yayınevi, Kitapta Bölüm.