A new time invariant fuzzy time series forecasting method based on particle swarm optimization CH Aladag, U Yolcu, E Egrioglu, AZ Dalar Applied Soft Computing 12 (10), 3291-3299, 2012 | 153 | 2012 |
Median-Pi artificial neural network for forecasting E Egrioglu, U Yolcu, E Bas, AZ Dalar Neural Computing and Applications, 307-316, 2019 | 41 | 2019 |
Probabilistic forecasting, linearity and nonlinearity hypothesis tests with bootstrapped linear and nonlinear artificial neural network U Yolcu, E Egrioglu, E Bas, OC Yolcu, AZ Dalar Journal of Experimental & Theoretical Artificial Intelligence 33 (3), 383-404, 2021 | 20 | 2021 |
A new fuzzy time series method based on an ARMA-type recurrent Pi-Sigma artificial neural network C Kocak, AZ Dalar, OC Yolcu, E Bas, E Egrioglu Soft Computing 24 (11), 8243–8252, 2020 | 20 | 2020 |
Application of Type-1 Fuzzy Functions Approach for Time Series Forecasting CH Aladag, IB Turksen, AZ Dalar, E Egrioglu, U Yolcu TJFS: Turkish Journal of Fuzzy Systems 5 (1), 01-09, 2014 | 20 | 2014 |
AR–ARCH Type Artificial Neural Network for Forecasting BS Corba, E Egrioglu, AZ Dalar Neural Processing Letters 51 (1), 819-836, 2020 | 18 | 2020 |
Bootstrap Type-1 Fuzzy Functions Approach for Time Series Forecasting AZ Dalar, E Egrioglu Trends and Perspectives in Linear Statistical Inference, 69-87, 2018 | 11 | 2018 |
Single Multiplicative Neuron Model Artificial Neuron Network Trained by Bat Algorithm for Time Series Forecasting E Bas, U Yolcu, E Egrioglu, O Cagcag Yolcu, AZ Dalar American Journal of Intelligent Systems 6 (3), 74-77, 2016 | 8 | 2016 |
A hybrid high order fuzzy time series forecasting approach based on PSO and ANNS methods E Egrioglu, CH Aladag, U Yolcu, AZ Dalar Am. J. Intell. Syst 6 (1), 8, 2016 | 8 | 2016 |
A New Neural Network Model with Deterministic Trend and Seasonality Components for Time Series Forecasting E Egrioglu, CH Aladag, U Yolcu, E Bas, AZ Dalar Advances in Time Series Forecasting: Volume 2, 76-92, 2017 | 5 | 2017 |
Parçacık sürü optimizasyonuna dayalı bulanık zaman serisi yaklaşımı AZ Dalar Fen Bilimleri Enstitüsü, 2012 | 2 | 2012 |
A Hybrid Forecasting Method Based On Exponential Smoothing and Multiplicative Neuron Model Artificial Neural Network E Egrioglu, U Yolcu, E Baş, AZ Dalar 3rd INTERNATIONAL RESEARCHERS, STATISTICIANS AND YOUNG STATISTICIANS …, 2017 | 1 | 2017 |
A New Hybrid Fuzzy Time Series Forecasting Approach Based on Intelligent Optimization E Egrioğlu, CH Aladag, U Yolcu, AZ Dalar American Journal of Intelligent Systems 5 (4), 97-108, 2015 | 1 | 2015 |
An Experimental Study for Transforming and Differencing Effects in Multiplicative Neuron Model Artificial Neural Network for Time Series Forecasting D Ilter, E Karaahmetoglu, O Gundogdu, AZ Dalar The 8th International Days of Statistics and Economics, Prague, 2014 | 1 | 2014 |
An Investigation of Differencing Effect in Multiplicative Neuron Model Artificial Neural Network for Istanbul Stock Exchange Time Series Forecasting AZ Dalar, E Eğrioğlu, U Yolcu, D İlter, Ö Gündoğdu American Journal of Intelligent Systems 4 (1), 15-19, 2014 | 1 | 2014 |
COMPARISON OF SINGLE MULTIPLICATIVE NEURON ARTIFICIAL NEURAL NETWORK MODELS USING ABC AND BP TRAINING ALGORITHMS F ALPASLAN, E EĞRİOĞLU, Ç ALADAĞ, D İLTER, A DALAR Anadolu Üniversitesi Bilim Ve Teknoloji Dergisi A-Uygulamalı Bilimler ve …, 2013 | 1 | 2013 |
Type-1 Fuzzy Functions Approach based on the Particle Swarm Optimization for Time Series Forecasting AZ Dalar The 17th International Days of Statistics and Economics, 177-126, 2023 | | 2023 |
Super Learner Yöntemi ile BIST100 Endeksi Öngörüsünün Elde Edilmesi AZ Dalar, AZ Çelenli Başaran, Ö Gündoğdu İktisadi ve İdari Bilimlerde Araştırma ve Değerlendirmeler, 41-54, 2023 | | 2023 |
A New Journal for Forecasting Research E Egrioglu, U Yolcu, E Bas, AZ Dalar, OC Yolcu Turkish Journal of Forecasting 1 (2), 72-74, 2017 | | 2017 |
Fuzzy Functions Approach for Time Series Forecasting AZ Dalar, E Egrioglu, U Yolcu, CH Aladag Advances in Time Series Forecasting: Volume 2, 144-155, 2017 | | 2017 |