Person: YILMAZ, GÜNEŞ
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YILMAZ
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GÜNEŞ
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Publication Detection and analysis of driver fatigue stages with eeg signals(Pamukkale Univ, 2022-01-01) Eken, Recep; Yılmaz, Güneş; YILMAZ, GÜNEŞ; Demir, Ahmet; DEMİR, AHMET; Bekiryazıcı, Şule; BEKİRYAZICI, ŞULE; Coşkun, Oğuzhan; Mühendislik Fakültesi; Elektrik ve Elektronik Mühendisliği Bölümü; 0000-0003-1115-186X; 0000-0001-8972-1952; GZM-6710-2022; AAH-4177-2021; AAH-4182-2021Today, many people die in traffic accidents. Sleeplessness and fatigue of drivers are shown as the most important cause of traffic accidents. For this reason, research on driver performance analysis is of great importance. In this study, a system is designed to analyze driver fatigue using electroencephalography (EEG) data. As the data set, the EEG signals from sustained-attention driving task prepared by National Chiao Tung University have been used. The data set is divided into four classes to determine the driver's fatigue times and level. In order to determine the frequency ranges that occur during driver fatigue phases, EEG signals are filtered. Principal Component Analysis method has been used to reduce the size of the features matrix. With the Divide and Conquer algorithm, all combinations in which the four classes will be separated best are determined and classification has been done at each step using sub-classifiers. As sub-classifiers, k-Nearest Neighborhood, Support Vector Machines and Linear Discrimination Analysis algorithms are used. As a result of the study, the average classification successes are 87.9% for the k-Nearest Neighborhood algorithm, 88.5% for the Support Vector Machines algorithm and 81.6% for Linear Discrimination Analysis. The highest classification success has been achieved as 93.2% with the Support Vector Machines classifier, between 67.5-90 min. of driving at the 4th grade fatigue level.Publication Comparison of the evolutionary algorithm's performances on power flow analysis(Pamukkale Univ, 2018-01-01) Kuyu, Yiğit Çağatay; KUYU, YİĞİT ÇAĞATAY; Erdem, Nergis; ERDEM, NERGİS; Vatansever, Fahri; VATANSEVER, FAHRİ; Yılmaz, Güneş; YILMAZ, GÜNEŞ; Mühendislik Fakültesi; Elektrik ve Elektronik Mühendisliği Bölümü; 0000-0002-3885-8622; 0000-0001-8972-1952; AAG-8425-2021; AAC-6923-2021; AAH-4182-2021; AAH-4017-2021Power flow in energy systems is one of the major problems. Several classical analysis methods are utilized for solving this problem. However, power generation limits, valve loading effects of units also makes the power flow problem become much harder to solve in the system. In this case, it is possible to achieve the most appropriate solutions with evolutionary algorithms. In this study, optimal power flow problems are solved under same beginning conditions, comprehensively performed with evolutionary algorithms which are recently used and associated algorithm performance is analyzed in IEEE 30-bus test system for two cases. Energy gains of algorithms are obtained; the best, worst and mean values found from optimization are evaluated; convergence analyses are performed comparatively. Thus the effectiveness and efficiency of evolutionary algorithms are clearly demonstrated on solution of optimal power flow problems.Publication Influence of temperature on detectable minimum rotation rate in i-fogs using er-doped sfss(Slovak Univ Technology, 2022-04-01) GÜNDAY, ABDURRAHMAN; YILMAZ, GÜNEŞ; Sağ, Emirhan; Mühendislik Fakültesi; Elektrik ve Elektronik Mühendisliği Bölümü; 0000-0002-2030-4357; 0000-0001-8972-1952; AAH-5448-2021; AAH-4182-2021In this study, an interferometric fiber optic gyroscope (I-FOG) model exploiting the double-pass backward (DPB) erbiumdoped superfluorescent fiber source (SFS) with both thin-film filter (TFF) and fiber bragg grating (FBG) reflectors has been constructed and the effects of temperature variations on mean wavelength and detectable minimum rotation rate (DMRR) have been theoretically analyzed. the simulations corresponding with the relations between these parameters for temperature variations in the range of -60 degrees C to + 90 degrees C, have been performed using Matlab 2021b. DMRR variations have been found as 6.01 ppm/K and 3.83 ppm/K for the system with TFF, whilst they are 15.31 ppm/K and 1.58 ppm/K for the system with FBG.Publication Feature selection and analysis EEG signals with sequential forward selection algorithm and different classifiers(Ieee, 2020-01-01) Bekiryazıcı, Şule; Demir, Ahmet; Yılmaz, Güneş; BEKİRYAZICI, ŞULE; DEMİR, AHMET; YILMAZ, GÜNEŞ; Mühendislik Fakültesi; Elektrik Elektronik Mühendisliği Bölumü; 0000-0003-1115-186X; 0000-0001-8972-1952; AAH-4182-2021; AAH-4177-2021; KPP-7123-2024In this study, we investigated the features that could best represent EEG signals for brain computer interface systems and classifier accuracy was compared using different classification methods. EEG signals data set were taken from "BCI II Competition". In this study, inadequate features that reduce classification accuracy were determined by using sequential forward selection algorithms and were extracted from real-dimensional feature matrix. The remaining active feature matrix and real-dimensional feature matrix were classified using k-nearest neighbor, subspace K-nearest neighbor, support vector machines, subspace discriminant and random forest decision tree algorithms. As a result of this study, the highest classification accuracy of real-dimensional feature matrix was obtained as 83.8% by random forest decision tree algorithm. In the other, the highest classification accuracy of dimention reductioned feature matrix with sequential forward selection algorthm was obtained as 96.4% by random forest decision tree algorithm.Publication Investigation of the atmospheric attenuation factors in FSO communication systems using the taguchi method(Hindawi, 2020-03-12) Demir, Pelin; Yılmaz, Güneş; DEMİR, PELİN; YILMAZ, GÜNEŞ; Mühendislik Fakültesi; Elektrik Elektronik Mühendisliği Bölümü; 0000-0001-9768-4194; 0000-0001-8972-1952; ABG-5204-2021; JCE-7740-2023In this study, Mie and Rayleigh scattering in free space optics (FSO) communication systems were investigated in terms of the atmospheric attenuation. Because of the movement of the Earth, the communication distance and surrounding gas densities are inconsistent in each region. This change leads to atmospheric attenuation and then data losses and inefficient communication in FSO occur. Therefore, the density change and distance must be calculated in each communication once the data is transmitted. In the literature, it was observed that the atmospheric attenuation is regarding some FSO communication parameters such as transmission distance, visibility, and scatter particle size distribution, the number of particles per unit volume, scatter cross-sectional area, and wavelength. Besides, in real-time communication, it is necessary to update FSO parameters simultaneously. However, this updating process for all parameter takes a long time to adapt to a new position. This paper proposes the design of the experiment method (Doe) to determine the severity of the FSO parameters. And Taguchi's Doe method allows analyzing of FSO communication system parameters to avoid long calculation time. Results show that the proposed method helps in understanding the priorities of the parameters in FSO and reducing the updating time.