16. Egrioglu E., Fildes R., Bas E., Recurrent fuzzy time series functions approaches for forecasting. Granular Computing, 2021. https://doi.org/10.1007/s41066-021-00257-3
15. Bas E., Yolcu U., Egrioglu E., Intuitionistic fuzzy time series functions approach for time series forecasting, Granular Computing, 2020. (Early Access)
14. Egrioglu E., Yolcu U., Bas E., Intuitionistic high order fuzzy time series forecasting method based on pi-sigma artificial neural networks trained by artificial bee colony, Granular Computing, 4 (4), 639-654, 2019.
13. Bas E., Egrioglu E., Yolcu U., Grosan C., Type 1 fuzzy function approach based on ridge regression for forecasting, Granular Computing, 4 (4), 629-637, 2019.
12. Akdeniz E., Egrioglu E., Bas E., Yolcu U. An ARMA type Pi-Sigma artificial neural network for nonlinear time series forecasting, Journal of Artificial Intelligence and Soft Computing Research, 8(2), 121-132, 2018.
11. Bas E., Egrioglu E., Uslu V.R. Shrinkage parameters for each explanatory variable found via particle swarm optimization in ridge regression, Peertechz Journal of Computer Science and Engineering, 2(1), 012-020, 2017.
10. Bas, E., Yolcu, U., Egrioglu, E., Cagcag Yolcu O., Dalar A.Z., Single Multiplicative Neuron Model Artificial Neuron Network Trained By Bat Algorithm For Time Series Forecasting, American Journal of Intelligent Systems, 6(3): 74-77, 2016.
9. Yolcu U., Bas E., The Forecasting Of Labour Force Participation And The Unemployment Rate In Poland And Turkey Using Fuzzy Time Series Methods, Comparative Economic Research, 19(2): 5-25, 2016.
8. Egrioglu E., Bas E., Aladag C.H., Yolcu U., Probabilistic Fuzzy Time Series Method Based On Artificial Neural Network, American Journal Of Intelligent Systems, 6(2): 42-47, 2016.
7. Bas E., The Training Of Multiplicative Neuron Model Based Artificial Neural Networks With Differential Evolution Algorithm For Forecasting, Journal of Artificial Intelligence and Soft Computing Research, 6(1): 5-11, 2016.
6. Bas E., Yolcu U., Egrioglu E., Aladag C.H., A Fuzzy Time Series Forecasting Method Based On Operation Of Union And Feed Forward Artificial Neural Network, American Journal of Intelligent Systems, 5(3): 81-91, 2015.
5. Bas E., Uslu V.R., Yolcu U., Egrioglu E., A Fuzzy Time Series Approach Using De/Best/1 Mutation Strategy Of Differential Evolution Algorithm, Aloy Journal Of Soft Computing And Applications, 2(2): 60-69, 2014.
4. Egrioglu E., Aladag C.H., Yolcu U., Bas E., A New Adaptive Network Based Fuzzy Inference System For Time Series Forecasting, Aloy Journal Of Soft Computing And Applications, 2(1): 25-32, 2014.
3. Uslu V.R., Egrioglu E., Bas E., Finding Optimal Value For The Shrinkage Parameter In Ridge Regression Via Particle Swarm Optimization, American Journal Of Intelligent Systems, 4(4): 142-147, 2014.
2. Uslu V.R., Bas E., Yolcu U., Egrioglu E., A New Fuzzy Time Series Analysis Approach By Using Differential Evolution Algorithm And Chronologically-Determined Weights, Journal Of Social And Economic Statistics, 2(1): 18-30, 2013.
1. Bas E., Uslu V.R., Yolcu U., Egrioglu E., A Fuzzy Time Series Analysis Approach By Using Differential Evolution Algorithm Based On The Number Of Recurrences Of Fuzzy Relations, American Journal Of Intelligent Systems, 3(2): 75-82, 2013.