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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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Shear performance of FRP Reinforced Deep Beams Made of Ultra High Performance Concrete (UHPC)
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The effect of Dopamine Agonists on patients with advanced Parkinson's disease subjected to subthalamic deep brain stimulation. (c2000)
Published 2000“…The mean levodopa dose was reduced by 90% (p < 0.01), while the mean dopamine agonist dose was increased by 15% from preoperative level. …”
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masterThesis -
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation
Published 2023“…Deep RL is utilized to model the EV chargers and the EV users. …”
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Electric vehicles charging management using deep reinforcement learning considering vehicle-to-grid operation and battery degradation
Published 2023“…Deep RL is utilized to model the EV chargers and the EV users. …”
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FLACON: A Deep Federated Transfer Learning-Enabled Transient Stability Assessment During Symmetrical and Asymmetrical Grid Faults
Published 2024“…In practice, TSA based on deep learning is preferable for its high accuracy but often overlooks challenges in maintaining data privacy while coping with network topology changes. …”
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Combining Saliency with Prediction for Endoscopic Diagnosis
Published 2020Get full text
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On the sampling and integration rates of process noise
Published 1995“…It is shown that the covariance of a sampled zero-mean exponentially-correlated process is independent of the sampling rate. …”
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A robust experimental-based artificial neural network approach for photovoltaic maximum power point identification considering electrical, thermal and meteorological impact
Published 2020“…The results showed a decrease in the MSE of V<sub>mp</sub> by 74.3% (from 1.6 V to 0.411 V), and in the MSE of I<sub>mp</sub> by 95% (from 4.4e−6 A to 2.16e−7 A), respectively. …”
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Artificial neural network algorithms. (c1999)
Published 1999Get full text
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Data-Efficient Wheat Disease Detection Using Shifted Window Transformer: Enhancing Accuracy, Sustainability, and Global Food Security
Published 2025“…This research presents a deep learning technique based on the Shifted Window (Swin) Transformer, a powerful attention-based model that effectively captures both local and global information for enhanced classification output. …”
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Improving pediatric trauma care: an automated system for wrist trauma detection using GELAN
Published 2025“…The results of our study highlight the capacity of deep learning to improve the diagnosis of pediatric trauma, decrease the burden on radiologists, and boost patient outcomes.…”
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Energy-Efficient Cell Association and Load Balancing for Low Battery Users in Heterogeneous Cellular Networks
Published 2025“…This paper proposes improved cell association schemes based on the battery levels of UE and Deep Q-learning (DQL) to achieve load balancing and to decrease the power consumption of Low Battery Users (LBUs). …”
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Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers
Published 2020“…<p dir="ltr">Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the coordinated charging supports flattening the load profile. …”
