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Full-Text Articles in Engineering
Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu
Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
Solar energy systems (SES) and photovoltaic (PV) modules should be operated at the maximum power point (MPP) to achieve the highest efficiency in the energy generation processes. Maximum power point tracking (MPPT) applications using conventional methods may not be able to follow the global MPP (GMPP) of the PV system under changing atmospheric conditions and they could oscillate around the local MPP. In this study, a machine learning and deep learning (DL) based long short-term memory (LSTM) model is proposed as an innovative solution for MPPT. Contrary to the traditional MPPT applications using current and voltage sensors, the output resistance …
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Development Of A Hybrid System Based On Abc Algorithm For Selection Of Appropriate Parameters For Disease Diagnosis From Ecg Signals, Ersi̇n Ersoy, Gazi̇ Erkan Bostanci, Mehmet Serdar Güzel
Turkish Journal of Electrical Engineering and Computer Sciences
The number of people who die due to cardiovascular diseases is quite high. In our study, ECG (electrocar-diogram) signals were divided into segments and waves based on temporal boundaries. Signal similarity methods such as convolution, correlation, covariance, signal peak to noise ratio (PNRS), structural similarity index (SSIM), one of the basic statistical parameters, arithmetic mean and entropy were applied to each of these sections. In addition, a square error-based new approach was applied and the difference of the signs from the mean sign was taken and used as a feature vector. The obtained feature vectors are used in the artificial …
A Novel Hybrid Algorithm For Morphological Analysis: Artificial Neural-Net-Xmor, Ayla Kayabaş, Ahmet Ercan Topcu, Özkan Kiliç
A Novel Hybrid Algorithm For Morphological Analysis: Artificial Neural-Net-Xmor, Ayla Kayabaş, Ahmet Ercan Topcu, Özkan Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a novel algorithm that combines a rule-based approach and an artificial neural network-based approach in morphological analysis. The usage of hybrid models including both techniques is evaluated for performance improvements. The proposed hybrid algorithm is based on the idea of the dynamic generation of an artificial neural network according to two-level phonological rules. In this study, the combination of linguistic parsing, a neural network-based error correction model, and statistical filtering is utilized to increase the coverage of pure morphological analysis. We experimented hybrid algorithm applying rule-based and long short-term memory-based (LSTM-based) techniques, and the results …