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Toplam kayıt 7, listelenen: 1-7
Long Short-Term Memory Network-based Speed Estimation Model of an Asynchronous Motor
(IEEE (Institute of Electrical and Electronics Engineers), 2021)
In this paper, an effective deep rotor speed estimation model of an asynchronous motor is presented. The estimation model is based on the long short-term memory (LSTM) network which is one of the deep learning models. The ...
A novel ship classification network with cascade deep features for line-of-sight sea data
(2021)
In ship classifcation, selecting distinctive features and designing a proper classifer are two key points of the process. As
a lack of most of the studies, these two essential points are considered separately. In this ...
A Novel Short-Term Photovoltaic Power Forecasting Approach based on Deep Convolutional Neural Network
(2021)
In this study, a novel photovoltaic power forecasting system that utilizes a deep Convolutional Neural Network (CNN) structure and an input signal decomposition algorithm is proposed. The proposed CNN architecture extracts ...
An improved residual-based convolutional neural network for very short-term wind power forecasting
(ELSEVIER, 2021)
An accurate forecast of wind power is very important in terms of economic dispatch and the operation of power systems. However, effectively mitigating the risks arising from wind power in power system operations greatly ...
Altitude and Attitude Control of a Quadcopter Based on Neuro-Fuzzy Controller
(Springer Science and Business Media Deutschland GmbH, 2022)
In this paper, a 6-degrees of freedom (DoF) nonlinear dynamic model of the quadcopter is derived and a robust altitude and attitude control is proposed. The motion control is performed with four neuro-fuzzy controllers ...
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 ...
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 ...