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- BildiriYalnız künye2018Quality lignite coal detection with discrete wavelet transform, discrete fourier transform, and ANN based on k-means clustering method
Korkmaz, Sevcan Aytac; Esmeray, Furkan; Varol, A.; Karabatak, M.; Varol, C.
In this article, the lignite coal datas in the Kalburcayi area of the Sivas-Kangal Basin have been used. This original data obtained from Kalburcayi area of the Sivas-Kangal Basin consists of 66 observations in the lignite coal area, including lignite quality parameters such as moisture content, ash, sulfur content and calorific value. These lignite coal datas have been clustered in two group with k-means method according to calori values. This clustering lignite coal data is classified by the Artifical Neural Network (ANN) classifier. In addition, Discrete Fourier Transform (DFT) and Discrete Wavelet Transform (DWT) have been applied to coal data for ANN classifiers. DFT-ANN, DWT-ANN, and ANN classification success results are compared. The highest classification success rate was found by DWT-ANN method.
AtıfScopus8OpenAlex12
İncele - BildiriYalnız künye2015Harmonic Analysis in Power Systems With Discrete Fourier Transform
Akmaz, Duzgun; Mamis, Mehmet Salih
Harmonics has become more significant issue due to the increasing of utilization of the non-linear loads and switching elements such as inverter on the power system recently. Harmonics disrupts the shape of the current and voltage signals in power systems and leads to many problems in power systems. It has made harmonic analysis necessary on the power system. Harmonics has become more significant issue due to the increasing of utilization of the non-linear loads and switching elements such as inverter on the power system recently. In this study a method is designed to obtain a basic signal by using Discrete Fourier Transform (DFT) in order to determine harmonics on power systems. The simulation of this method has been implemented by using Matlab/Simulink software package.
AtıfWoS2
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