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Full-Text Articles in Physical Sciences and Mathematics
Tourism Demand Modelling And Forecasting Using Data Mining Techniques In Multivariate Time Series: A Case Study In Turkey, Selçuk Cankurt, Abdülhami̇t Subaşi
Tourism Demand Modelling And Forecasting Using Data Mining Techniques In Multivariate Time Series: A Case Study In Turkey, Selçuk Cankurt, Abdülhami̇t Subaşi
Turkish Journal of Electrical Engineering and Computer Sciences
In this study multiple linear regression, multilayer perceptron (MLP) regression, and support vector regression (SVR) are used to make multivariate tourism forecasting for Turkey. This paper is a comparative study of data mining techniques based on multivariate regression modelling with monthly data points to forecast tourism demand; it focuses on Turkey. Both MLP and SVR methods are widely employed in the variety forecasting problems. Most of the previous research on tourism forecasting used univariate time series or a limited number of variables with mostly yearly or quarterly, and rarely monthly frequencies. However, the application of data mining techniques for multivariate …
Process Time And Mppt Performance Analysis Of Cf, Lut, And Ann Control Methods For A Pmsg-Based Wind Energy Generation System, Abdulhaki̇m Karakaya, Ercüment Karakaş
Process Time And Mppt Performance Analysis Of Cf, Lut, And Ann Control Methods For A Pmsg-Based Wind Energy Generation System, Abdulhaki̇m Karakaya, Ercüment Karakaş
Turkish Journal of Electrical Engineering and Computer Sciences
Due to environmental issues such as global warming and the greenhouse effect, there is a growing interest in renewable sources of energy. Wind energy, which is the most important of these energy sources, can potentially meet a portion of the global energy demand. Numerous studies are being conducted worldwide to determine how the maximum level of power can be obtained from wind energy. In these studies, there is a particular interest in permanent magnet synchronous generators (PMSGs). This is because PMSGs exhibit a good performance within a wide range wind speeds and can be driven directly. In this study, the …
Prediction-Based Reversible Image Watermarking Using Artificial Neural Networks, Mahsa Afsharizadeh, Majid Mohammadi
Prediction-Based Reversible Image Watermarking Using Artificial Neural Networks, Mahsa Afsharizadeh, Majid Mohammadi
Turkish Journal of Electrical Engineering and Computer Sciences
In prediction-based reversible watermarking schemes, watermark bits are embedded in the prediction errors. An accurate prediction results in smaller prediction errors, more efficient embedding, and less distortion for the watermarked image. In this paper, an accurate prediction is made using artificial neural networks. Before the embedding operation, 2 neural networks are trained by the pixel values of the image. Then the trained neural networks predict the pixel values that are used in the embedding operation. Due to the training ability of the neural networks, the prediction will be more accurate than the averaging technique. Experimental results show that the proposed …
Classification Of Short-Circuit Faults In High-Voltage Energy Transmission Line Using Energy Of Instantaneous Active Power Components-Based Common Vector Approach, Mehmet Yumurtaci, Gökhan Gökmen, Çağri Kocaman, Semi̇h Ergi̇n, Osman Kiliç
Classification Of Short-Circuit Faults In High-Voltage Energy Transmission Line Using Energy Of Instantaneous Active Power Components-Based Common Vector Approach, Mehmet Yumurtaci, Gökhan Gökmen, Çağri Kocaman, Semi̇h Ergi̇n, Osman Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
The majority of power system faults occur in transmission lines. The classification of these faults in power systems is an important issue. In this paper, the real parameters of a 28 km, 154 kV transmission line between Simav and Demirci in Turkey's electricity transmission network is simulated in MATLAB/Simulink. Wavelet packet transform (WPT) is applied to instantaneous voltage signals. Instantaneous active power components are obtained by multiplying instantaneous currents obtained from a voltage source side with these WPT-based voltage signal components. A new feature vector extraction scheme is employed by calculating the energies of instantaneous active power components. Constructed feature …
A Novel Approach Of Design And Analysis Of Fractal Antenna Using A Neurocomputational Method For Reconfigurable Rf Mems Antenna, Paras Chawla, Rajesh Khanna
A Novel Approach Of Design And Analysis Of Fractal Antenna Using A Neurocomputational Method For Reconfigurable Rf Mems Antenna, Paras Chawla, Rajesh Khanna
Turkish Journal of Electrical Engineering and Computer Sciences
A mathematical neural approach/artificial neural network (ANN) for the design of a swastika-shaped reconfigurable antenna as a feedforward side is proposed. Further design parameter calculations using the reverse procedure of the above method is presented. Neural network computational is one of the optimization methods that could be considered to improve the performance of the device. In this paper, the proposed planar antenna up to the 2nd iteration is simulated using finite element method-based HFSS software. The developed ANN algorithm method allows the optimization of the antenna to be carried out by exchanging repetitive simulations and also provides reduced processing times …