Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2019Scopus SJRQ3/r/munzur/3606
  Hybrid parliamentary optimization and big bang-big crunch algorithm for global optimization

  Kiziloluk, Soner; Özer, Ahmet Bedri

  Researchers have developed different metaheuristic algorithms to solve various optimization problems. The efficiency of a metaheuristic algorithm depends on the balance between exploration and exploitation. This paper presents the hybrid parliamentary optimization and big bang-big crunch (HPO-BBBC) algorithm, which is a combination of the parliamentary optimization algorithm (POA) and the big bang-big crunch (BB-BC) optimization algorithm. The intragroup competition phase of the POA is a process that searches for potential points in the search space, thereby providing an exploration mechanism. By contrast, the BB-BC algorithm has an effective exploitation mechanism. In the proposed method, steps of the BB-BC algorithm are added to the intragroup competition phase of the POA in order to improve the exploitation capabilities of the POA. Thus, the proposed method achieves a good balance between exploration and exploitation. The performance of the HPO-BBBC algorithm was tested using well-known mathematical test functions and compared with that of the POA, the BB-BC algorithm, and some other metaheuristics, namely the genetic algorithm, multiverse optimizer, crow search algorithm, dragonfly algorithm, and moth-flame optimization algorithm. The HPO-BBBC algorithm was found to achieve better optimization performance and a higher convergence speed than the above-mentioned algorithms on most benchmark problems.

  AtıfScopus3·WoS1·OpenAlex3

  İncele
• MakaleAçık Erişim2019Scopus SJRQ3/r/munzur/3418
  Fuzzy-logic-based robust speed control of switched reluctance motor for low and high speeds

  Omaç, Zeki

  Switched reluctance motor (SRM) is operated at high magnetic saturation to generate large torque. The flux linkage of SRM is a nonlinear function with phase current and rotor position because of the high magnetic saturation. Also, the performance of the speed controller for the SRM driver system can be negatively affected by noise, disturbances, and inertia of load torque. Therefore, the fuzzy speed controller for the SRM driver system was developed in this study. In addition, a dynamic model of SRM was simulated in Matlab/Simulink software. Based on the results obtained in this study, the speed of the SRM was controlled over a wide range of speeds including low and high speeds by the fuzzy speed controller. Furthermore, in simulation, the rotor speed was simulated depending on the reference speed. Moreover, the speed of the SRM was experimentally tested using the DS1103 Ace kit. Finally, simulation results were compared with experimental results and they were found to be consistent with each other.

  AtıfScopus10·WoS5·OpenAlex9·TR Dizin3

  İncele
• MakaleAçık Erişim2017Scopus SJRQ3/r/munzur/681
  Fault location determination for transmission lines with different series-compensation levels using transient frequencies

  Akmaz, Duzgun; Mamiş, Mehmet Salih; Arkan, Muslum; Tagluk, Mehmet Emin

  In this paper, based on the theory of traveling waves, the fault distances on long transmission lines with various series-compensation levels are determined using transient current and voltage frequencies. Transmission lines with series compensation are modeled using Alternative Transients Program software with frequency-dependent effects on the line included in the simulation. The transient current and voltage signals are obtained from the model. A fast Fourier transform is used for frequency-domain conversion and fault location is estimated from the frequencies of fault-generated harmonics in the transient spectrum. The algorithm is implemented in MATLAB. To investigate the effect of compensation on accuracy, the results are obtained for different series-compensation levels. The undesirable source-inductance effect is removed and estimation accuracy is further improved using a waveform-relaxation method. The method is found to be successful in determining fault location on series-compensated transmission lines. The effects of the compensation level, fault resistance, and phase angle are investigated.

  AtıfScopus6·WoS6·OpenAlex7

  İncele
• MakaleAçık Erişim2016Scopus SJRQ2/r/munzur/4499
  Sensorless field oriented control of nonsinusoidal flux-distribution permanent magnet synchronous motor with a FEM based ANN observer

  Öksüztepe, Eyyup; Omaç, Zeki; Polat, Mehmet; Çelik, Hakan; Selçuk, Ahmet Hakan; Kürüm, Hasan

  İncele
• MakaleAçık Erişim2015Scopus SJRQ2/r/munzur/4187
  Automatic classification of harmonic data using k-means and least square support vector machine

  Eristi, Huseyin; Tümen, Vedat; Yildirim, Ozal; Eristi, Belkis; Demir, Yakup

  In this paper, an effective classification approach to classify harmonic data has been proposed. In the proposed classifier approach, harmonic data obtained through a 3-phase system have been classified by using k-means and least square support vector machine (LS-SVM) models. In order to obtain class details regarding harmonic data, a k-means clustering algorithm has been applied to these data first. The training of the LS-SVM model has been realized with the class details obtained through the k-means algorithm. To increase the efficiency of the LS-SVM model, the regularization and kernel parameters of this model have been determined with a grid search method and the training phase has been realized. Backpropagation neural network and J48 decision tree classifiers have been applied to the same data and results have been obtained for the purpose of comparing the performance of the LS-SVM model. The real data obtained from the output of distribution system have been used to assess the performance of the proposed classifier system. The obtained results and comparisons suggest that the proposed classifier system approach is quite efficient at classifying harmonic data.

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  AtıfWoS1·OpenAlex3

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