Protecting inverter-based resources (IBRs) presents a considerable challenge due to their low fault current. This paper introduces an innovative protection scheme designed to enhance the security of inverter-based res...
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Current source inverters (CSI) are a promising candidate for connecting intermittent photovoltaic systems to medium voltage grids. Traditional PV systems require additional bulky low-frequency step-up transformers. CS...
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This study examines how fast rise times, which are common in modern power electronics and drive systems, affect the aging of electric machine windings. It focuses on how to ensure these windings can last longer and wo...
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The efficient management of agricultural resources requires a deep understanding of plant growth dynamics. This research focuses on Sweden's forestry sector and explicitly addresses the crucial early stages of pin...
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Recent advances have spotlighted the use of unmanned aerial vehicles (UAVs) for defense and surveillance, focusing on cooperative monitoring and exploration. However, these UAV systems face significant operational cha...
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Wind power is one of the sustainable ways to generate renewable *** recent years,some countries have set renewables to meet future energy needs,with the primary goal of reducing emissions and promoting sustainable gro...
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Wind power is one of the sustainable ways to generate renewable *** recent years,some countries have set renewables to meet future energy needs,with the primary goal of reducing emissions and promoting sustainable growth,primarily the use of wind and solar *** achieve the prediction of wind power generation,several deep and machine learning models are constructed in this article as base *** regression models are Deep neural network(DNN),k-nearest neighbor(KNN)regressor,long short-term memory(LSTM),averaging model,random forest(RF)regressor,bagging regressor,and gradient boosting(GB)*** addition,data cleaning and data preprocessing were performed to the *** dataset used in this study includes 4 features and 50530 *** accurately predict the wind power values,we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization(SFSPSO)to optimize the parameters of LSTM *** evaluation criteria were utilized to estimate the efficiency of the regression models,namely,mean absolute error(MAE),Nash Sutcliffe Efficiency(NSE),mean square error(MSE),coefficient of determination(R2),root mean squared error(RMSE).The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R2 equals 99.99%in predicting the wind power values.
Adversarial training is one of the predominant techniques for training classifiers that are robust to adversarial attacks. Recent work, however has found that adversarial training, which makes the overall classifier r...
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All individuals have a unique gait signature, or walking style, that can serve as their biometric identifier. While recent research has shown that deep neural networks can perform effective gait recognition, these stu...
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This research aims to transform mental health care by addressing critical gaps in existing systems and making support universally accessible free of cost. A centralized platform with a dynamic website has been develop...
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Digital reviews provide real-world feedback on products and services in an era of online commerce and access to information. Providing feedback fosters trust and credibility among potential customers, enabling them to...
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