Yazar "TR19915" için Bilgisayar Mühendisliği Bölümü listeleme
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A Hybrid artificial intelligence method to classify trichotillomania and obsessive compulsive disorder
Erguzel, Turker Tekin; Tan, Oguz; Tarhan, Nevzat; Ozekes, Serhat; Hizli Sayar, Gokben (2015-02)Classification of psychiatric disorders is becoming one of the major focuses of research using artificial intelligence approach. The combination of feature selection and classification methods generates satisfactory ... -
A Hybrid PSO-PID Approach For Trajectory Tracking Application of A Liquid Level Control Process
Erguzel, Turker Tekin (2015-06)Water level control is a crucial step for steam generators (SG) which are widely used to control the temperature of nuclear power plants. The control process is therefore a challenging task to improve the performance ... -
A Wrapper-Based Approach For Feature Selection And Disorder Classification
Erguzel, Turker Tekin; Tas, Cumhur; Cebi, Merve (2015-06-22)Feature selection (FS) and classification are consecutive artificial intelligence (AI) methods used in data analysis, pattern classification, data mining and medical informatics. Beside promising studies in the application ... -
Analysis of Brain Functional Changes in High-Frequency Repetitive Transcranial Magnetic Stimulation in Treatment-Resistant Depression
Ozekes, Serhat; Erguzel, Turker Tekin; Hizli Sayar, Gokben; Tarhan, Nevzat (Clinical EEG & Neuroscience, 2014)Repetitive transcranial magnetic stimulation (rTMS) is a treatment procedure that uses magnetic fields to stimulate nerve cells in the brain, and is associated with significant improvements in clinical symptoms of major ... -
Ant Colony Optimization Based Feature Selection Method for QEEG Data Classification
Erguzel, Turker Tekin; Ozekes, Serhat; Gultekin, Selahattin; Tarhan, Nevzat (Psychiatry Investigation, 2014)Objective:Many applications such as biomedical signals require selecting a subset of the input features in order to represent the whole set of features. A feature selection algorithm has recently been proposed as a new ... -
ARTIFICIAL INTELLIGENCE APPROACH TO CLASSIFY UNIPOLAR and BIPOLAR DEPRESSIVE DISORDERS
Erguzel, Turker Tekin; Tarhan, Nevzat; Hizli Sayar, Gokben (2015)Machine learning (ML) approaches for medical decision making processes are valuable when both high classification accuracy and less feature requirements are satisfied. Artificial neural networks ... -
Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach
Erguzel, Turker Tekin; Ozekes, Serhat; Tan, Oguz; Gultekin, Selahattin (Clinical EEG and Neuroscience, 2014)Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an optimized classification method was tested in 147 patients with major ... -
Neural Network Based Response Prediction of rTMS in Major Depressive Disorder Using QEEG Cordance
Erguzel, Turker Tekin; Gultekin, Selahattin; Tarhan, Nevzat; Bayram, Ali; Ozekes, Serhat; Hizli Sayar, Gokben (2015-01-12)ObjectiveaaThe combination of repetitive transcranial magnetic stimulation (rTMS), a non-pharmacological form of therapy for treating major depressive disorder (MDD), and electroencephalogram (EEG) is a valuable tool for ... -
Process Control Using Genetic Algorithm And Ant Colony Optimization Algorithm
Erguzel, Turker Tekin; Akbay, Erbil (Journal of Intelligent Fuzzy Systems, 2014)Artificial life uses biological knowledge and techniques to solve different engineering, management, control and computational problems. Natural systems teach us that very simple individual organisms can form systems ...