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Recurrent Multiplicative Neuron Model Artificial Neural Network for Non-Linear Time Series Forecasting 

Egrioglu, Erol; Yolcu, Ufuk; Aladag, Cagdas Hakan; Bas, Eren (Elsevier Science Bv, 2014)
Artificial neural networks (ANN) have been widely used in recent years to model non-linear time series since ANN approach is a responsive method and does not require some assumptions such as normality or linearity. An ...

Forecasting Nonlinear Time Series With A Hybrid Methodology 

Aladag, Cagdas Hakan; Egrioglu, Erol; Kadilar, Cem (Pergamon-Elsevier Science Ltd, 2009)
In recent years, artificial neural networks (ANNs) have been used for forecasting in time series in the literature. Although it is possible to model both linear and nonlinear structures in time series by using ANNs, they ...

Improving Weighted Information Criterion By Using Optimization 

Aladag, Cagdas Hakan; Egrioglu, Erol; Gunay, Suleyman; Basaran, Murat A. (Elsevier Science Bv, 2010)
Although artificial neural networks (ANN) have been widely used in forecasting time series, the determination of the best model is still a problem that has been studied a lot. Various approaches available in the literature ...

A New Multilayer Feedforward Network Based on Trimmed Mean Neuron Model 

Yolcu, Ufuk; Bas, Eren; Egrioglu, Erol; Aladag, Cagdas Hakan (Acad Sciences Czech Republic, Inst Computer Science, 2015)
The multilayer perceptron model has been suggested as an alternative to conventional approaches, and can accurately forecast time series. Additionally, several novel artificial neural network models have been proposed as ...
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AuthorAladag, Cagdas Hakan (4)
Egrioglu, Erol (4)
Bas, Eren (2)Yolcu, Ufuk (2)Basaran, Murat A. (1)Gunay, Suleyman (1)Kadilar, Cem (1)SubjectMathematics (2)Business & Economics (1)Computer Science (1)... View MoreDate Issued2009 (1)2010 (1)2014 (1)2015 (1)Has File(s)Yes (4)

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