Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2024Scopus SJRQ2/r/munzur/1799
  Hybrid Deep Learning Model for Earthquake Time Prediction

  Utku, Anıl; Akcayol, Muhammet Ali

  Earthquakes are one of the most dangerous natural disasters that have constantly threatened humanity in the last decade. Therefore, it is extremely important to take preventive measures against earthquakes. Time estimation in these dangerous events is becoming more specific, especially in order to minimize the damage caused by earthquakes. In this study, a hybrid deep learning model is proposed to predict the time of the next earthquake to potentially occur. The developed CNN+GRU model was compared with RF, ARIMA, CNN and GRU. These models were tested using an earthquake dataset. Experimental results show that the CNN+GRU model performs better than others according to MSE, RMSE, MAE and MAPE metrics. This study highlights the importance of predicting earthquakes, providing a way to help take more effective precautions against earthquakes and potentially minimize loss of life and material damage. This study should be considered an important step in the methods used to predict future earthquakes and supports efforts to reduce earthquake risks.

  AtıfScopus6·WoS5·TR Dizin4

  İncele
• MakaleAçık Erişim2023Scopus SJRQ3/r/munzur/1683
  Rotor Field-Oriented Control of Doubly Fed Induction Generator in Wind Energy Conversion System

  Omac, Zeki; Erdem, Irfan

  In this study, robust and high-performance vector control of a rotor side converter (RSC) was performed for stability and efficient operation doubly fed induction generator (DFIG) based on the variable speed wind turbine (VSWT). The mathematical model of the DFIG is simulated in the computer. Amplitude and frequency of the voltage in the DFIG were controlled for different values of load and variable speeds. In the experimental study, a DFIG-based wind turbine system was set up in the laboratory. The field position of the stator was detected from stator voltages by a phase-locked loop (PLL) circuit. The rotor position was measured with an incremental encoder connected to the rotor shaft of the DFIG. The angular position of the slip was calculated by the difference between the rotor and the stator field positions. The frequency and amplitude of rotor currents were determined with the angular position of slip. To generate output voltages of converter feeding rotor windings, the space vector pulse width modulation (SVPWM) technique was used. In the experimental study, the RSC was controlled with the DS1103 board. The prepared experiment set was tested at different operating speeds.

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  AtıfScopus4·WoS3·OpenAlex4

  İncele
• MakaleAçık Erişim2023Scopus SJRQ3/r/munzur/1635
  Effect of Spectrogram Parameters and Noise Types on The Performance of Spectro-temporal Peaks Based Audio Search Method

  Koseoglu, Murat; Uyanik, Hakan

  Audio search algorithms are used to detect the queried file in large databases, especially in multimedia applications. These algorithms are expected to perform the detection in a reliable and robust way within the shortest time. In this study, based on spectral peaks method, an audio fingerprint algorithm with a few minor modifications was developed to detect the matching audio file in target database. This method has two stages as the audio fingerprint extraction and matching. In the first stage, fingerprint features are extracted from spectral peaks on the spectrograms of audio files by hash functions. This state-of-art technique reduces the processing load and time considerably compared to traditional methods. In the second stage, fingerprint data of the queried file are compared with the data created in the first stage in the database. The algorithm was demonstrated, and the effect of spectrogram parameters (window size, overlap, number of FFT) was investigated by considering reliability and robustness under different noise sources. Also, it was aimed to contribute to new audio retrieval studies based on spectral peaks method. It was observed that the variation in the spectrogram parameters significantly affected the number of matchings, reliability and robustness. Under high noise conditions, the optimal spectrogram parameters were determined as 512 (window size), 50% (overlap), 512 (number of FFT). It was seen in general that the algorithm successfully detected the queried file in the database even in high noise conditions for these parameters. No significant effect of music genre was observed.

  AtıfScopus9·WoS6·OpenAlex11·TR Dizin1

  İncele
• MakaleAçık Erişim2020Scopus SJRQ3/r/munzur/3270
  A new family of archimedean copula via trigonometric generator function

  Susam, Selim Orhun

  In this paper, new type of Archimedean copula based on cotangent generator function, and dependence characteristics are investigated. Also, the estimation procedure of the dependence parameter is given. A Monte Carlo study is performed to measure the performance of estimators. To demonstrate the goodness of fit performance of the new family, a real data analysis is performed.

  AtıfScopus13·WoS10·OpenAlex11·TR Dizin1

  İncele
• MakaleYalnız künye2015Scopus SJRQ3/r/munzur/4790
  A Time Series Approach for Precipitation in Turkey

  Balibey, Mesut; Türkyilmaz, Serpil

  The climate that has a dynamic structure varies continuously. Basic climatological features of any region depend on many meteorological variables, such as precipitation and temperature records. The changes in these two variables reveal important clues about climate variations. Turkey is one of the sensitive areas for climate variation around the world. In this study, statistical analysis is applied to historical data set consisted of monthly precipitation totals (mm.) which are provided by the Turkish State Meteorological Service(TSMS) for 1999-2010 period in Turkey. Furthermore, a sinusoidal model for each region obtained by using a time series method is proposed in order to obtain a sinusoidal form for the precipitation to each region. Besides a basic form of Frequency Domain Techniques, usual Box-Jenkins ARIMA approach is applied in this study. In conclusion, it is observed that the sinusoidal model predictions are more appropriate than ARIMA techniques and usual generalized linear model (GLM) techniques.

  AtıfWoS6

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