Yazar "Tezcan, Suleyman Sungur" seçeneğine göre listele

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    A novel hybrid global optimization algorithm having training strategy: hybrid Taguchi-vortex search algorithm
    (Tubitak Scientific & Technological Research Council Turkey, 2021) Saka, Mustafa; Coban, Melih; Eke, Ibrahim; Tezcan, Suleyman Sungur; Taplamacioglu, Muslum Cengiz
    In this paper, a novel hybrid Taguchi-vortex search algorithm (HTVS) is proposed for solving global optimization problems. Taguchi orthogonal approximation and vortex search algorithm (VS) are hybridized in presenting method. In HTVS, orthogonal arrays in the Taguchi method are trained and obtained better solutions are used to find global optima in VS. Thus, HTVS has better relation between exploration and exploitation, and it exhibits more powerful approximation to find global optimum value. Proposed HTVS algorithm is applied to sixteen well-known benchmark optimization test functions with different dimensions. The results are compared with the Taguchi orthogonal array approximation (TOAA), vortex search algorithm, grey wolf optimizer (GWO), sine cosine algorithm (SCA), moth-flame optimization algorithm (MFO), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). In order to compare the effectiveness of HTVS statistically, Wilcoxon signed-rank test (WSRT) is used in this study. Furthermore, HTVS is applied to two different real engineering problems having some constraints (tension/compression spring design and pressure vessel design). All obtained results suggested that HTVS can find optimal or very close to optimal results. Moreover, it has good computational ability and fast convergence behavior as well.
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    Öğe
    Analysing the Effect of Metaheuristic Based Feature Selection Algorithms on the Classification of the Power Quality Events
    (Kırıkkale Üniversitesi, 2024) Gümüş, Birsen; Çoban, Melih; Tezcan, Suleyman Sungur
    In this study, two different optimization algorithms have been used for the feature selection stage, which plays a crucial role in the classification of power quality disturbances. In the first part of the study, signals containing power quality events were generated to initiate the classification process. Discrete wavelet transform (DWT) has been used for feature extraction. Two different datasets were obtained by normalizing and taking logarithm of the dataset obtained after the feature extraction process. The Equilibrium Optimizer (EO) and the Salp Swarm Optimization Algorithm (SSA), which are named metaheuristic based feature selection algorithms, were used for the feature selection process. The K Nearest Neighbour Algorithm (KNN) is preferred for classification. The highest accuracy rate in classification was achieved at 96.05% when utilizing EO as the feature selection algorithm and using the logarithmic dataset. The lowest classification accuracy rate was obtained as 90.62% when the feature selection algorithm was SSA and the normalized data set was used. In the second part of the study, a histogram graph was created to identify the most frequently selected features from the first part. The highest accuracy rate obtained for the classification using the histogram graph was observed to be 95.8% and the lowest accuracy rate was 93.83%.
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    Economic Load Dispatch Using Vortex Search Algorithm
    (Ieee, 2017) Saka, Mustafa; Eke, Ibrahim; Tezcan, Suleyman Sungur; Taplamacioglu, M. Cengiz
    Economic load dispatch (ELD) is one of most fundamental issue for energy generation and distribution in power systems. For this purpose, different optimization techniques are developed and applied to ELD problem. In this paper, vortex search algorithm (VSA) is proposed and used for solving ELD problem. VSA method was developed from nature by observing the state of stirring liquids. Transmission losses, valve point loading effect, ramp rate limits and prohibited operating zone constraints are considered to solve ELD problem with VSA method. The feasibility and effectivity of this method is demonstrated for different cases. Obtained results are compared with different developed algorithms and these results clearly point out that proposed VSA method gives successfully outputs.
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    Gravitational Search Algorithm (GSA) Based PID Controller Design for Two Area Multi-Source Power System Load Frequency Control (LFC)
    (Gazi Univ, 2018) Safi, Shah Jahan; Tezcan, Suleyman Sungur; Eke, Ibrahim; Farhad, Zakirhussain
    This paper presents the design and performance analysis of a meta-heuristic search technique (Gravitational-Search-algorithm) for optimal tuning of Proportional-Integral-Derivative plus Filter (PIDF) controller for automatic generation control of multi-source two area interconnected power system. Integral of absolute magnitude of square of error (IASE) is used as objective function. Excellency of the proposed approach is shown with comparison of differential evolution and particle swarm optimization algorithm. The dynamic response has been studied under variety of operating-conditions. The simulation results by MATLAB/Simulink program represent that the tuned PIDF-controllers by gravitational search algorithm supply the better damping of oscillations in power system.
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    A Robust PID Power System Stabilizer Design of Single Machine Infinite Bus System using Firefly Algorithm
    (Gazi Univ, 2018) Farhad, Zakirhussain; Eke, Ibrahim; Tezcan, Suleyman Sungur; Safi, Shah Jahan
    This paper presents the design of a proportional-integral-derivative power-system-stabilizer using the firefly algorithm for tuning of stabilizer parameters and washout (reset). The proposed optimization of parameters is carried out with eigenvalue analysis based objective function for two cases (two parametric bounds) to guarantee the stability for the single-machine-infinite-bus system model for a wide range of operating conditions. The system performance with Firefly-Algorithm tuned controller is compared with Bat-Algorithm optimized Conventional-Power-System-Stabilizer controller. The power system robustness is tested on 133 operating conditions to set up the superior performance of FA-PID-PSS over the BA-CPSS. According to the eigenvalue analysis and time response parameters results, it is found that BA-CPSS and FA-PID-PSS (case-I) have the ability to stabilize the system for some operating conditions; but the FA-PID-PSS (case-II) can stabilize the system and can improve settling time and overshoot for all operating conditions.
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    Solving economic load dispatch problem with valve-point effects using filled function
    (Gazi Univ, Fac Engineering Architecture, 2017) Eke, Ibrahim; Tezcan, Suleyman Sungur; Celik, Coskun
    This paper presents a filled function method to solve economic load dispatch (ELD) of the thermal unit. The proposed method can take care of ELD considering nonlinearity such as valve point loading. The effectiveness of the proposed algorithm has been verified on three different test systems with equality and inequality constraint. Simulation results show that the filled function method is less sensitive to initial values of parameters and is more effective than other previously developed algorithms. In addition, the proposed algorithm is highly promising for the large-scale system.