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Toplam kayıt 18, listelenen: 11-18
SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting
(Elsevier, 2021)
Photovoltaic (PV) power generation has high uncertainties due to the randomness and imbalance nature of solar energy and meteorological parameters. Hence, accurate PV power forecasts are essential in the operation of PV ...
Deep rhythm and long short term memory-based drowsiness detection
(Elsevier, 2021)
In this paper, a deep-rhythm-based approach is proposed for the efficient detection of drowsiness based on EEG recordings. In the proposed approach, EEG images are used instead of signals where the time and frequency ...
A new semi-analytical approach for self and mutual inductance calculation of hexagonal spiral coil used in wireless power transfer systems
(Springer, 2021)
Several methods have been proposed in the literature for the calculation of self and mutual inductance. These methods include the use of complex integral analysis, the necessity of having primary and secondary coils with ...
An efficient fault classification method in solar photovoltaic modules using transfer learning and multi-scale convolutional neural network
(Elsevier, 2022)
Photovoltaic (PV) power generation is one of the remarkable energy types to provide clean and sustainable energy. Therefore, rapid fault detection and classification of PV modules can help to increase the reliability of ...
Two-stepped majority voting for efficient EEG-based emotion classification
(Springer, 2020)
In this paper, a novel approach that is based on two-stepped majority voting is proposed for efficient EEG-based emotion classification. Emotion recognition is important for human-machine interactions. Facial features- and ...
COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images
(Elsevier, 2020)
The Coronavirus Disease 2019 (COVID-19) outbreak has a tremendous impact on global health and the daily life of people still living in more than two hundred countries. The crucial action to gain the force in the fight of ...
When machine learning meets fractional-order chaotic signals: detecting dynamical variations
(Elsevier, 2022)
The challenge of classifying multivariate time series generated by discrete and continuous dynamical systems according to their chaotic or non-chaotic behavior has been studied extensively in the literature. The examination ...
A Novel Analog Modulation Classification: Discrete Wavelet Transform-Extreme Learning Machine (DWT-ELM)
(Bitlis Eren Üniversitesi, 2021)
The aim of this study is to propose a method using discrete wavelet transform and extreme learning machine (DWT-ELM) in classification of communication signals. Six types of analog modulated signals as “AM”, “DSB”, “USB”, ...