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Full-Text Articles in Physical Sciences and Mathematics
Short-Term Load Forecasting Without Meteorological Data Using Ai-Based Structures, İdi̇l Işikli Esener, Tolga Yüksel, Mehmet Kurban
Short-Term Load Forecasting Without Meteorological Data Using Ai-Based Structures, İdi̇l Işikli Esener, Tolga Yüksel, Mehmet Kurban
Turkish Journal of Electrical Engineering and Computer Sciences
STLF is used in making decisions about economical power generation capacity, fuel purchasing, safety assessment, and power system planning in order to have economical power conditions. In this study, Turkey's 24-hour-ahead load forecasting without meteorological data is studied. ANN, wavelet transform and ANN, wavelet transform and RBF NN, and EMD and RBF NN structures are used in STLF procedures. Local holidays' historical load data are changed into data with normal day characteristics, and the estimation results of these days are not included in error computation. To obtain more accurate results, a regulation on forecasted loads is proposed. Regulated and unregulated …
An E-Nose-Based Indoor Air Quality Monitoring System: Prediction Of Combustible And Toxic Gas Concentrations, Beki̇r Mumyakmaz, Keri̇m Karabacak
An E-Nose-Based Indoor Air Quality Monitoring System: Prediction Of Combustible And Toxic Gas Concentrations, Beki̇r Mumyakmaz, Keri̇m Karabacak
Turkish Journal of Electrical Engineering and Computer Sciences
A system for monitoring and predicting indoor air quality level is proposed in this paper. The system comprises a computer with a monitoring program and a sensor cell, which has an array of metal oxide gas sensors along with a temperature and humidity sensor. The gas sensors in the cell have been chosen to detect only hydrogen, methane, and carbon monoxide gases. Methane was selected as a representative for indoor combustible gases, and carbon monoxide was used to represent indoor toxic gases. Hydrogen was used as an interfering (and also combustible) gas in the study. A number of experiments were …
Forecasting The Day-Ahead Price In Electricity Balancing And Settlement Market Of Turkey By Using Artificial Neural Networks, Mehmet Ali̇ Kölmek, İsa Navruz
Forecasting The Day-Ahead Price In Electricity Balancing And Settlement Market Of Turkey By Using Artificial Neural Networks, Mehmet Ali̇ Kölmek, İsa Navruz
Turkish Journal of Electrical Engineering and Computer Sciences
In determination of electric energy price, most price information coming from bilateral contracts is effective, but the importance of the spot market (pool market) price cannot be ignored. Forecasting the spot market price is very crucial, especially for companies actively participating in the spot market and giving purchase and sale bids. An artificial neural network is a way frequently used for price forecasting research. In this study, simulation studies about price modeling via artificial neural networks and proper artificial neural network configurations are examined. After selection of different network topologies and parameters, attempts are made to observe network performance by …
Epilepsy Diagnosis Using Artificial Neural Network Learned By Pso, Nesi̇be Yalçin, Gülay Tezel, Ci̇han Karakuzu
Epilepsy Diagnosis Using Artificial Neural Network Learned By Pso, Nesi̇be Yalçin, Gülay Tezel, Ci̇han Karakuzu
Turkish Journal of Electrical Engineering and Computer Sciences
Electroencephalogram (EEG) is used routinely for diagnosis of diseases occurring in the brain. It is a very useful clinical tool in the classification of epileptic seizures and the diagnosis of epilepsy. In this study, epilepsy diagnosis has been investigated using EEG records. For this purpose, an artificial neural network (ANN), widely used and known as an active classification technique, is applied. The particle swarm optimization (PSO) method, which does not need gradient calculation, derivative information, or any solution of differential equations, is preferred as the training algorithm for the ANN. A PSO-based neural network (PSONN) model is diversified according to …
A Comparative Study Of Two Different Fpga-Based Arrhythmia Classifier Architectures, Ahmet Turan Özdemi̇r, Kenan Danişman
A Comparative Study Of Two Different Fpga-Based Arrhythmia Classifier Architectures, Ahmet Turan Özdemi̇r, Kenan Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
Early diagnosis of dangerous heart conditions is very important for the treatment of heart diseases and for the prevention of sudden cardiac death. Automatic electrocardiogram (ECG) arrhythmia classifiers are essential to timely diagnosis. However, most of the medical diagnosis systems proposed in the literature are software-based. This work focused on the hardware implementation of a mobile artificial neural network (ANN)-based arrhythmia classifier that is implemented on a field programmable gate array (FPGA) as a single chip solution, as an alternative to various software models of ANNs. Due to the parallel nature of ANNs, hardware implementation of ANNs needs a large …