2025

  1. Ağraz, M., Eğrioğlu, E., Baş, E., Chen, M.-Y., Göksülük, D., & Burak, M. F. (2025). Diabetes development prediction using a hybrid model combining dendritic artificial neuron model and logistic regression. Endocrinology Research and Practice, 29(2), 84–93. https://doi.org/10.5152/erp.2025.24585
  2. Bas, E., & Egrioglu, E. (2025). A new automatic forecasting method based on explainable deep dendritic artificial neural network. Scientific Reports, 15(1), Article 44830. https://doi.org/10.1038/s41598-025-29042-x
  3. Bas, E., & Egrioglu, E. (2025). Robust picture fuzzy regression functions approach based on M-estimators for the forecasting problem. Computational Economics, 65(5), 2775–2810. https://doi.org/10.1007/s10614-024-10647-9
  4. Cansu, T., Bas, E., Akkan, T., & Egrioglu, E. (2025). A new hybrid recurrent intuitionistic fuzzy time series forecasting method. Forecasting, 7(4), Article 71. https://doi.org/10.3390/forecast7040071
  5. Dalar, A. Z., & Egrioglu, E. (2025). Blending traditional and novel techniques: Hybrid type-1 fuzzy functions for forecasting. Engineering Applications of Artificial Intelligence, 148, Article 110445. https://doi.org/10.1016/j.engappai.2025.110445
  6. Ahıskalı, A., Akkan, T., & Bas, E. (2025). Evaluation of a new approach in water quality assessments using the modified VIKOR method. Environmental Modeling & Assessment, 30(3), 613–623. https://doi.org/10.1007/s10666-025-10020-6
  7. Hatipoğlu, B., & Doğru, F. Z. (2025). Joint modelling location and scale with the LTS estimation method. Journal of Statistical Computation and Simulation, 95(6), 1208–1225. https://doi.org/10.1080/00949655.2024.2449112
  8. Karakus, H., Dogru, F. Z., & Akgul, F. G. (2025). Unit power Lindley distribution: Properties and estimation. Gazi University Journal of Science, 38(1), 502–526. https://doi.org/10.35378/gujs.1432128
  9. Gül, H. H. (2025). Improved maximum likelihood estimators for the parameters of the two-parameter lindley distribution. Sigma Journal of Engineering and Natural Sciences, 43(1), 290–300. https://doi.org/10.14744/sigma.2025.00022
  10. Gül, H. H. M., Ercan, H., Akınoğlu, B., & Açıkgöz, Ş. (2025). A retrospective assessment of Türkiye’s recent energy policy in terms of energy security and climate change mitigation. Energies, 18(4), Article 951. https://doi.org/10.3390/en18040951
  11. Gul, H. H., & Yeniay Koçer, N. (2025). Estimation of the Gompertz distribution’s parameters under folded ranked set sampling. Sigma Journal of Engineering and Natural Sciences, 43(3), 737–747.  https://doi.org/10.14744/sigma.2025.00068
  12. Djongmon, K., & Okur, N. (2025). On a generalized q-binomial distribution and new q-multinomial distribution. Communications in Statistics - Theory and Methods, 54(19), 6277–6294. https://doi.org/10.1080/03610926.2025.2453545
  13. Celenli Basaran, A. Z., Gundogdu, O., & Dalar, A. Z. (2025). Robust Treynor ratio for portfolio selection. Annals of Operations Research. Baskıdaki Makale. https://doi.org/10.1007/s10479-025-06863-7
  14. Dalar, A. Z., & Egrioglu, E. (2025). Blending traditional and novel techniques: Hybrid type-1 fuzzy functions for forecasting. Engineering Applications of Artificial Intelligence, 148, Article 110445. https://doi.org/10.1016/j.engappai.2025.110445
  15. Turhan, S., Dalar, A. Z., & İşcan, İ. (2025). Analyzing Hermite-Hadamard inequalities: The role of simulations in geometrically (s,P)-functions. Journal of Inequalities and Applications, 2025(1), Article 152. https://doi.org/10.1186/s13660-025-03361-z
  16. Topsir, A., Agraz, M., & Cebi, S. (2025). Machine learning-based detection of cost manipulation fraud in financial statements. 2025 International Conference on Decision Aid Sciences and Applications (DASA), 656–660.   https://doi.org/10.1109/DASA68193.2025.11499058
  17. Topsir, A., Narayanan, C., Agraz, M., & Choudhary, G. (2025). SAFE: A semi-agent system integrating feature selection, PubMed literature mining, and pathway enrichment. 2025 International Conference on Decision Aid Sciences and Applications (DASA), 1501–1505.   https://doi.org/10.1109/DASA68193.2025.11498978
  18. Topşir, A., Güler, F., Çetin, E., Burak, M. F., & Ağraz, M. (2025). Thyroid disease classification using generative adversarial networks and Kolmogorov-Arnold network for three-class classification. BMC Medical Informatics and Decision Making, 25(1), Article 284.  https://doi.org/10.1186/s12911-025-03014-7
  19. Ağraz, M., Eğrioğlu, E., Baş, E., Chen, M.-Y., Göksülük, D., & Burak, M. F. (2025). Diabetes development prediction using a hybrid model combining dendritic artificial neuron model and logistic regression. Endocrinology Research and Practice, 29(2), 84–93. https://doi.org/10.5152/erp.2025.24585
  20. Özgül, F., Semiz, K., & Eğrioğlu, E. (2025). Preservice physical education teachers’ attitudes toward the use of distance education environments and online self-regulation: Descriptive research. Türkiye Klinikleri Spor Bilimleri Dergisi, 17(3), 198–205.
  21. Karakuş, H., Doğru, F. Z., & Akgül, F. G. (2025). Unit power Lindley distribution: Properties and estimation. Gazi University Journal of Science, 38(1), 502–526.
  22. Dalar, A. Z. (2025). Zaman serisi öngörüsü için derin bulanık fonksiyonlar yaklaşımı. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 26(4), 680–698.
  23. Güler, F., & Ağraz, M. (2025). Investigation of binary and multiclass classification performance of skin cancer images using transfer learning methods. Journal of Clinical Practice and Research, 47(3), 235–245.
  24. Akyol, U., & Gül, M. (2025). Türkiye’de yabancılara konut satışının MARS yöntemi ile tahmin edilmesi. Karadeniz Fen Bilimleri Dergisi, 15(1), 498–518.
  25. Aksakal, S. Ş., & Eğrioğlu, E. (2025). A hybrid forecasting method based on the exponential smoothing and multiplicative neuron model artificial neural network. Turkish Journal of Forecasting, 37–43.
  26. Aksakal, S. Ş., & Eğrioğlu, E. (2025). Modified Holt’s linear trend method based on particle swarm optimization. Turkish Journal of Forecasting, 44–50.
  27. Karahasan, O., Bas, E., & Egrioglu, E. (2025). A hybrid deep recurrent artificial neural network with a simple exponential smoothing feedback mechanism. Information Sciences, 686, Article 121356. https://doi.org/10.1016/j.ins.2024.121356
  28. Kolemen, E., Egrioglu, E., Bas, E., & Turkmen, M. (2025). A new hybrid neural network based on gated recurrent unit and simple exponential smoothing for forecasting. Computing, 107(10), Article 196. https://doi.org/10.1007/s00607-025-01549-1
  29. Rahmi, I., Efendi, R., Samat, N. A., Yanuar, F., Yozza, H., Wahyudi, M., Burney, S. M. A., & Eğrioğlu, E. (2025). Essentials of preprocessing data in improving logistic regression performance based on rough sets theory: A case study of stunting in West Sumatra, Indonesia. Journal of Science and Mathematics Letters, 13(1), 124–139. https://doi.org/10.37134/JSML.VOL13.1.12.2025
  30. Sahin, H., Karacelik, A. A., Kaltalioglu, K., Bas, E., & Egrioglu, E. (2025). Assessment of extraction conditions on phenolic compounds in Turkish pine honey. Emirates Journal of Food and Agriculture, 37. https://doi.org/10.3897/ejfa.2025.141957
  31. Demirel, E., & Gül, H. H. (2025). Maximum likelihood estimation for the inverted Kumaraswamy distribution based on the extreme ranked set sampling. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, 14(2), 952–970.
  32. Gül, H. H., & Yeniay Koçer, N. (2025). Çift sıralı küme örnekleme tasarımı altında Power Rayleigh dağılımı parametrelerinin farklı yöntemler ile tahmini. Sinop Üniversitesi Fen Bilimleri Dergisi, 10(1), 110–133.