Yazar "Çoban, Melih" seçeneğine göre listele

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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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    Öğe
    Electric fish optimization for economic load dispatch problem
    (2024) Yıldız, Yağmur Arıkan; Akkaş, Özge Pınar; Saka, Mustafa; Çoban, Melih; Eke, İbrahim
    The Economic Load Dispatch (ELD) problem is an essential aspect of power system planning and operational scheduling. Different techniques and algorithms have been recommended to solve it, aiming to minimize the cost of power generation with satisfying the load requirements. In this paper, a new algorithm called Electric Fish Optimization (EFO) is used to solve the ELD problem by considering the line losses, ramp rate limits, maximum and minimum capacities of the generators and prohibited operating zones (POZ). The algorithm has been utilized in test systems consisting of 6 and 15 units and its outcomes have been compared to those from previous research studies. The proposed algorithm has been shown to achieve minimum cost, indicating its superiority and effectiveness in addressing power system planning challenges. It is evident that the presented algorithm offers a valuable solution for optimizing ELD problems.