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Öğe A novel hybrid algorithm based on Stochastic Fractal Search Algorithm and CMA-ES(Düzce Üniversitesi, 2023) Paçacı, Serdar; Bingöl, Okan; Güvenç, UğurIn this study, a novel hybridization approach, which is called CMASFS and is based on the covariance matrix adaptation evolution strategy (CMA-ES) and the stochastic fractal search (SFS) algorithms. To make the proposed algorithm dynamic, Gaussian walk equations involved in the diffusion process of SFS have been updated and the algorithm decide to use which the Gaussian walk equations. The effectiveness of the proposed algorithm is tested using CEC2017 benchmark functions having unimodal, multimodal, hybrid, and composition functions in 10, 30, 50, and 100 dimensions. The performance of the CMASFS algorithm is compared with 17 metaheuristic algorithms given in the literature over the CEC2017 benchmark functions. According to the results, it is seen that CMASFS is generally obtained better mean error values. Moreover, to show the superiority of the proposed algorithm, Friedman analysis and the Wilcoxon rank-sum test are applied to the test results of the algorithms. The results of the Wilcoxon signed-rank test show that the improvement with the CMASFS algorithm is statistically significant on the majority of the CEC2017. The results of Friedman test verify that the CMASFS is obtained the best rank compared to both the original SFS and other compared algorithms.Öğe AC Chopper Application and Benefits of Auxiliary Windings for PSC Motors(Kaunas Univ Technology, 2013) Işık, Mehmet Fatih; Güvenç, Uğur; Yanmaz, HilmiIn this work, a novel driver circuit is designed for permanent split capacitor motors (PSC). With this driver circuit, semi-conductive technology is used in place of cumulative winding for this type of motors that are particularly used in kitchen exhaust fans. Developed circuit is controlled via PWM method. IGBT transistors are used for the power circuit. An optocoupler driver is designed and used in order to drive and trigger these IGBT transistors. Due to this reason, this work includes an electronic AC/AC chopper application that provides energy conservation and noise reduction by removing cumulative winding in currently used asynchronous motors with cumulative auxiliary winding stators and shaded pole motorsÖğe Active Power Loss Minimization in Electric Power Systems Through Artificial Bee Colony Algorithm(Praise Worthy Prize Srl, 2010) Çobanlı, Serkan; Öztürk, Ali; Güvenç, Uğur; Tosun, SalihReactive power optimization (RPO) is an important area of study to provide working for power systems in a secure and economical way. RPO is used for the voltage control, decreasing of active power losses, and for the optimization of the power coefficients. In RPO the non-linear power loss function is used as a purpose function to be minimized. The control parameters of that function are bus voltages of the generators, level settings of transformers and the reactive power output values of the capacitors added to buses. Artificial Bee Colony (ABC) algorithm, one of the intuitive methods is used in this optimization study. In this study, by using the ABC algorithm, RPO provided on the IEEE 6-bus and IEEE 30-bus test systems. The ABC algorithm is compared with some heuristic algorithms. It is shown by the results that active power losses can be decreased by ABC algorithm. Copyright (C) 2010 Praise Worthy Prize S.r.l - All rights reservedÖğe Anahtarlamalı relüktans motorun doğrudan moment denetimi(2009) Güvenç, Uğur; Sönmez, Yusuf; Yılmaz, Cemal; Sayan, H. HüseyinAnahtarlamalı Relüktans Motorlar (ARM) maliyetlerinin düşük ve denetiminin kolay olması sebebiyle motor sürücü endüstrisinde artan bir ilgiye sahiptirler. Ancak ARM’ nin doğrusal olmayan yapısından dolayı üretilen momentte yüksek dalgalanmalar meydana gelmektedir. Bu makalede, ARM’ deki moment dalgalanmalarının azaltılması için doğrudan moment denetimi gerçekleştirilmiştir. Tasarlanan yöntemde motor temel hızında çalışırken klasik PI denetleyiciye göre daha düzgün moment üretmektedir.Öğe Analysis, test and management of the metaheuristic searching process: an experimental study on SOS(2020) Kahraman, Hamdi Tolga; Aras, Sefa; Sönmez, Yusuf; Güvenç, Uğur; Gedikli, EyüpIn a search process, getting trapped in a local minimum or jumping the global minimum problems are also one of the biggestproblems of meta-heuristic algorithms as in artificial intelligence methods. In this paper, causes of these problems are investigatedand novel solution methods are developed. For this purpose, a novel framework has been developed to test and analyze the metaheuristic algorithms. Additionally, analysis and test studies have been carried out for Symbiotic Organisms Search (SOS)Algorithm. The aim of the study is to measure the mimicking a natural ecosystem success of symbiotic operators. Thus, problemsin the search process have been discovered and operators' design mistakes have been revealed as a case study of the developedtesting and analyzing method. Moreover, ways of realizing a precise neighborhood search (intensification) and getting rid of thelocal minimum (increasing diversification) have been explored. Important information that enhances the performance of operatorsin the search process has been achieved through experimental studies. Additionally, it is expected that the new experimental testmethods developed and presented in this paper contributes to meta-heuristic algorithms studies for designing and testing.Öğe Anisotropic diffusion filter without conductivity parameters(2012) Demirci, Recep; Güvenç, Uğur; Tanyeri, UfukTwo novel automatic anisotropic diffusion filters without conduction parameters were proposed in this paper. In the proposed first method, initially, the gradient of the noisy image to be filtered was calculated by Sobel operator and then the center of gravity of gradient image was used as diffusivity parameter, K and edge threshold. It was observed that the center of gravity of gradient image changed with noise. In the second approach, the complement of gradient image was directly employed as heat conductivity parameter in image filter. Consequently, the user dependency was avoided. The proposed image filter was tested with well-known test images. © 2012 Dunarea de Jos University.Öğe Application of gravitational search algorithm for optimal reactive power dispatch problem(2011) Duman, Serhat; Sönmez, Yusuf; Güvenç, Uğur; Yörükeren, NuranIn this paper, Gravitational Search Algorithm (GSA) is applied to solve the optimal reactive power dispatch (ORPD) problem. The ORPD problem is formulated as a nonlinear constrained single-objective optimization problem where the real power loss and the bus voltage deviations are to be minimized separately. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system consisting 6 generator and compared other algorithms reported those before in literature. Results show that GSA is more efficient than others for solution of single-objective ORPD problem. © 2011 IEEE.Öğe Application of STATCOM-supercapacitor for low-voltage ride-through capability in DFIG-based wind farm(Springer London Ltd, 2017) Döşoğlu, Mehmet Kenan; Arsoy, Aysen Basa; Güvenç, UğurLow-voltage problem emerges in cases of symmetrical and asymmetrical fault in power systems. This problem can be solved out by ensuring low-voltage ride-through capability of wind power plants, through a static synchronous compensator (STATCOM). The purpose of this study is to reveal that the system can be recovered well by inserting a STATCOM with energy storage to a bus where a double-fed induction generator (DFIG)-based wind farm has been connected, so the bus voltage is maintained within desired limits during a fault. Moreover, a supercapacitor is used as an energy storage element. Modeling of the DFIG and STATCOM along with the nonlinear supercapacitor was carried out in a MATLAB/Simulink environment. The behaviors of the system under three- and two-phase faults have been compared with and without STATCOM-supercapacitor, by observing the parameters of DFIG output voltage, active power, speed, electrical torque variations, and d-q axis stator current variations. It was found that the system became stable in a short time when the STATCOM-supercapacitor was incorporated into the full-order modeled DFIG.Öğe Application of Symbiotic Organisms Search Algorithm to Solve Various Economic Load Dispatch Problems(Ieee, 2016) Güvenç, Uğur; Duman, Serhat; Döşoğlu, M. Kenan; Kahraman, H. Tolga; Sönmez, Yusuf; Yılmaz, CemalThis paper proposes the application of Symbiotic Organisms Search (SOS) Algorithm to solve the various Economic Load Dispatch (ELD) problems. Both classical ELD problem which has smooth fuel cost function and nonconvex ELD problem which has nonconvex and discontinuous fuel cost function due to considering of some practical constraints like valve point effects, ramp rate limits and prohibited generating zones have been solved in the study. Three different test cases have been used to show the efficiency and reliability of the proposed algorithm. 38-unit test system has been used for classical ELD and 3-unit and 15-unit test systems have been used for nonconvex ELD problem. Results have been compared to various heuristic methods reported before in the literature and they show that proposed algorithm converges to the global optimum in early iterations and can produce superior results than others in the solution of ELD problems which have both smooth and nonconvex and discontinuous fuel cost function.Öğe Best Agent-specific Behavior: Improved Gravitational Search Algorithm(Tayfun UYGUNOĞLU, 2016) Katırcıoğlu, Ferzan; Güvenç, UğurGravitational Search Algorithm has a gravitational force between masses. The gravitational force is proportional to the mass of agents and inversely proportional to the square of the distance between them. Also, the direction of the force of attraction is the big object. So great mass agents move slowly. According to the approach Kbest, agents acting itself are selected from those with the best mass. This is means very massive agent such as other agents has an acceleration, a large changing velocity and substantially positions. Whereas, it had to move very slowly due from of the large mass and from having the best value. When agent that has the best value is found the total force in the next iteration, instead of Kbest, Kworstapplication is proposed. In Kworstapproach, by activating best agent to influence the worst mass with agents, the total force and therefore to a low velocity is intended. Increasing the convergence property values best results with the change in positionin a very small proportion is targeted.The obtained results are compared and evaluated with the standard YAA algorithmÖğe Bina Aydınlatmasının Ağ Tabanlı Tasarımı ve Bulanık Mantık İle Uzaktan Denetimi(2009) Yılmaz, Cemal; Koşalay, İlhan; Sönmez, Yusuf; Güvenç, Uğur; Üncü, İ. SerkanBu çalışmada, bir binanın aydınlatma sistemi ağ tabanlı olarak tasarlanmıştır. Tasarımda Profibus-DP ağ yapısı kullanılmıştır. Bina aydınlatmasının kontrolünde Bulanık Mantık Denetimi (BMD) kullanılmıştır. BMD uygulamasında, bina aydınlatma seviyelerini ölçen algılayıcılardan gelen bilgiler kullanılmıştır. Bu bilgiler Profibus-DP ağı üzerinden sisteme aktarılmıştır. Aydınlatma armatürlerinin Profibus-DP ağı üzerinden denetimi sağlanmıştır. Tasarlanan sistemde, bina içi aydınlatma ihtiyaç duyulan seviyede kalması sağlanmıştır. Tasarım ile, enerji tasarrufu ve sağlıklı aydınlatma imkanı elde edilmiştirÖğe Chaotic Moth Swarm Algorithm(Ieee, 2017) Güvenç, Uğur; Duman, Serhat; Hınıslıoğlu, YunusMoth Swarm Algorithm (MSA) is one of the newest developed nature-inspired heuristics for optimization problem. Nevertheless MSA has a drawback which is slow convergence. Chaos is incorporated into MSA to eliminate this drawback. In this paper, ten chaotic maps have been embedded into MSA to find the best numbers of prospectors for increase the exploitation of the best promising solutions. The proposed method is applied to solve the well-known seven benchmark test functions. Simulation results show that chaotic maps can improve the performance of the original MSA in terms of the convergence speed. At the same time, sinusoidal map is the best map for improving the performance of MSA significantly.Öğe Combined economic and emission dispatch solution using gravitational search algorithm(Elsevier Science Bv, 2012) Güvenç, Uğur; Sönmez, Yusuf; Duman, Serhat; Yörükeren, NuranIn this article, the Gravitational Search Algorithm (GSA) has been proposed to find the optimal solution for Combined Economic and Emission Dispatch (CEED) problems. It is aimed, in the CEED problem, that scheduling of generators should operate with both minimum fuel costs and emission levels, simultaneously, while satisfying the load demand and operational constraints. In this paper, the CEED problem is formulated as a multi-objective problem by considering the fuel cost and emission objectives of generating units. The bi-objective optimization problem is converted into a single objective function using a price penalty factor in order to solve it with GSA. The proposed algorithm has been implemented on four different test cases, having a valve point effect with transmission loss and having no valve point effect without transmission loss. In order to see the effectiveness of the proposed algorithm, it has been compared with other algorithms in the literature. Results show that the GSA is more powerful than other algorithms. (C) 2012 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.Öğe Combined economic emission dispatch solution using genetic algorithm based on similarity crossover(Academic Journals, 2010) Güvenç, UğurCombined economic emission dispatch (CEED) problem is to schedule the committed generating units outputs to meet the required load demand at minimum operating cost with minimum emission simultaneously. This multi-objective CEED problem is converted into a single objective function using a price penalty factor. In this paper, a novel Genetic Algorithm method based on similarity crossover for solving CEED problem in power systems is proposed. In the proposed method, children created by using similarity measurement between mother and father chromosomes relationship. The feasibility of the proposed approach is demonstrated for two different power systems, and it is compared in the recent literature. The study results show that the proposed approach is more efficient in finding higher quality solutions in CEED problems.Öğe COMPARISON OF THE EFFECTS OF IMAGE SEGMENTATION ON IMAGE PROCESSING PERFORMANCE WITH PARALLEL PROGRAMMING(Yildiz Technical Univ, 2017) Durgut, Aykut; Biroğul, Serdar; Güvenç, UğurIn this study, the difference between parallel programming and serial programming and the differences between whole image processing and image processing by segmentation was tried be to analysed. In the context of the study, to the image given to the application, which improved with Net framework, median, mean and gauss filters were applied by using single, double and 4 as a separate part serial programming and parallel programming methods. As a result of the study experienced in different computers and processors, it was noticed that parallel programming method performed filter processing in a shorter time both in the whole image and the segmented image. We determined that the whole image processing has higher performance than other method for image.Öğe A Comperative Study on Novel Machine Learning Algorithms for Estimation of Energy Performance of Residential Buildings(Ieee, 2015) Sönmez, Yusuf; Güvenç, Uğur; Kahraman, H. Tolga; Yılmaz, CemalThis study aims to improve the energy performance of residential buildings. heating load (HL) and cooling load (CL) are considered as a measure of heating ventilation and air conditioning (HVAC) system in this process. In order to achive an effective estimation, hybrid machine learning algorithms including, artificial bee colony-based k-nearest neighbor (abc-knn), genetic algorithm-based knn (ga-knn), adaptive artificial neural network with genetic algorithm (ga-ann) and adaptive ann with artificial bee colony (abc-ann) are used. Results are compared classical knn and ann methods. Thence, relations between input and target parameters are defined and performance of well-known classical knn and ann is improved substantialy.Öğe COYOTE OPTIMIZATION ALGORITHM TO SOLVE ENERGY HUB ECONOMIC DISPATCH PROBLEM(Isparta University of Applied Sciences, 2020) Güvenç, Uğur; Battal, OnurRegardless of energy type that we need today, it is important to use it efficiently and economically in the production, transmission and distribution stages. In line with the developing technology and needs, a new energy concept has emerged in which different energy types managed together in the past were managed independently. In this concept, energy infrastructures of more than one energy carrier such as electricity, gas and heat are met as Energy Hub (EH) to supply the demands such as electricity, gas, heating, cooling and compressed air by means of energy conversion, distribution and storage devices. EHs are expected to meet the demands energy with low operating costs. Energy hub economic dispatch problem (EHEDP) is a non-linear, non-convex, uniform and non-differential multidimensional optimization problem. In this study, the energy cost of the system is minimized by using the Coyote Optimization Algorithm (COA) for the solution of the EHEDP. The results obtained with COA have been compared with the results of heuristic algorithms such as Gravitational Search Algorithm (GSA), Enhanced Gravitational Search Algorithm (EGSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) in the literature. The compared results showed that COA performed better than other algorithms in solving EHED problem.Öğe Determination of the PID controller parameters for speed and position control of DC motor using gravitational search algorithm(2011) Duman, Serhat; Maden, Dinçer; Güvenç, UğurIn this paper we use a new search heuristic called Gravitational Search Algorithm (GSA) to determination of the optimal PID controller parameters in the speed and position control of a DC motor. The model of a DC motor is considered as second and third order system. Mean squared error (MSE) performance index has been used as objective function. End of the optimization process, the rise and the settling times and the overshoot are compared to those reported in the literature. To show that effectiveness of proposed method are compared with Ziegler-Nichols method in speed control of DC motor. Simulation results show the effectiveness and robustness of proposed controllers to provide the speed and position control of DC motor. © 2011 Chamber of Turkish Electric.Öğe Developing of Decision Support System for Land Mine Classification by Meta-heuristic Classifier(Ieee, 2016) Yılmaz, Cemal; Kahraman, Hamdi Tolga; Söyler, Salih; Sönmez, Yusuf; Güvenç, UğurIn this study, a decision support system has been developed for land mine detection and classification. Data obtained from detector based magnetic anomaly have been used to classify the land mines. With this classification, it is decided that whether obtained data belongs to a land mine or not, and the type of mine. The meta-heuristic k-NN classifier (HKC) has been used in developed decision support system. Consequently, it is seen that decision support system detects the presence of mines and decides the type of mine with 100% success for measurements in a certain range, and the proposed classifying method shows much higher performance than traditional instance-based classification method.Öğe Economic Dispatch Integrated Wind Power Using Coyote Optimization Algorithm(Ieee, 2019) Güvenç, Uğur; Kaymaz, EnesFossil fuels used in power system cause air pollution and global warming because of releasing greenhouse gases. Nowadays, renewable energy especially wind power has more widespread in power generation due to ecological concerns and increasing fuel prices. Therefore, it is presented the Economic Dispatch integrated wind power approach in this paper. However, wind power is stochastic because wind speed is uncertain in nature. Therefore Weibull Probability Density Function ( PDF) and Incomplete Gamma Function (IGF) are used to estimating and modelling wind power. To solve the problem effectively, Coyote Optimization Algorithm (COA) is implemented to the problem and it was tested on various power system consisting thermal generator and wind power generator. Simulation results generated by COA are compared with other heuristic algorithm such as GA and PSO. It can be clearly seen that COA produces better results than GA and PSO.
