A Genetic Algorithm Model Based On Dominant Gene Selection And Doping Operators

Aksu, Özgür
Kalınlı, Adem


Zerman, Emin; Konuk, Baris; NUR YILMAZ, GÖKÇE; Akar, Gözde (2014-10-30)
The increasing demand for streaming video raises the need for flexible and easily implemented Video Quality Assessment (VQA) metrics. Although there are different VQA metrics, most of these are either Full-Reference (FR) or Reduced-Reference (RR). Both FR and RR metrics bring challenges for on-the-fly multimedia systems due to the necessity of additional network traffic for reference data. No-eference (NR) video metrics, on the other hand, as the name suggests, are much more flexible for user-end applicatio...
A strength-biased prediction model for forecasting exchange rates using support vector machines and genetic algorithms
Ozorhan, Mustafa Onur; Toroslu, İsmail Hakkı; Şehitoğlu, Onur Tolga (2017-11-01)
This paper addresses problem of predicting direction and magnitude of movement of currency pairs in the foreign exchange market. The study uses Support Vector Machine with a novel approach for input data and trading strategy. The input data contain technical indicators generated from currency price data (i.e., open, high, low and close prices) and representation of these technical indicators as trend deterministic signals. The input data are also dynamically adapted to each trading day with genetic algorith...
A temporal neural network model for constructing connectionist expert system knowledge bases
Alpaslan, Ferda Nur (Elsevier BV, 1996-04-01)
This paper introduces a temporal feedforward neural network model that can be applied to a number of neural network application areas, including connectionist expert systems. The neural network model has a multi-layer structure, i.e. the number of layers is not limited. Also, the model has the flexibility of defining output nodes in any layer. This is especially important for connectionist expert system applications.
A data driven epidemic model to analyze and forecast the dynamics of COVID-19
Hasanli, Rza; Uğur, Ömür; Evcin, Cansu; Department of Scientific Computing (2021-8)
Due to recent evolution of the COVID-19 outbreak, accurate mathematical modelling to capture the dynamics of disease transmission is of vital importance. Since the availability and quality of data differs from region to region, it is very difficult to develop an accurate model from the global perspective. Nevertheless, local predictive models can be developed by collecting data from certain regions. In this thesis, a modified version of Susceptible-Exposed-Infected-Recovered-Dead (SEIRD) differential model ...
A physical model for dimensional reduction and its effects on the observable parameters of the universe
Karaca, Koray; Bayın, Selçuk; Department of Physics (2005)
In this thesis, assuming that higher spatial dimensions existed only during the inflationary prematter phases of the universe, we construct a (1+D)-dimensional (D>3), nonsingular, homogeneous and isotropic Friedmann model for dimensional reduction. In this model, dimensional reduction occurs in the form of a phase transition that follows from a purely thermodynamical consideration that the universe heats up during the inflationary prematter phases. When the temperature reaches its Planck value Tpl,D, which ...
Citation Formats
Ö. Aksu and A. Kalınlı, “A Genetic Algorithm Model Based On Dominant Gene Selection And Doping Operators,” 2009, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/87982.