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.
This paper explores the application of reinforcement learning (RL) to torpedo guidance with a focus on obstacle avoidance and target acquisition in dynamic environments. By employing a dual-actor network approach and ...
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Interior permanent magnet synchronous machines (IPMSMs) are widely used in industrial applications, electric propulsion and precision applications. Accurate and efficient simulations of IPMSM drives are essential for ...
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Advances in immunological research are essential for elucidating immune responses and developing targeted therapeutic approaches. This study proposes an automated method for immune cell classification leveraging machi...
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Time-synchronization (TS) formation control for unmanned surface vehicles (USVs) presents several advantages, including precise execution of tasks, broadened combat capabilities, and improved information fusion qualit...
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Time-synchronization (TS) formation control for unmanned surface vehicles (USVs) presents several advantages, including precise execution of tasks, broadened combat capabilities, and improved information fusion quality. To achieve this performance, a time-synchronized formation control method is presented that takes into account direct topology, external disturbances, and system uncertainties (EDSU). In contrast to prior formation control strategies, we introduce the formalized time-synchronized formation control framework, where all state components of the formation system concurrently converge to the equilibrium point at a uniform time constant, independently of their initial states. To counteract the EDSU, a fixed-time disturbance observer is designed to guarantee the convergence of all observer error components to zero. System stability is corroborated through the application of Lyapunov-like theory. Simulations and comparative experiments on three USVs are conducted to demonstrate the proposed method's superiority. IEEE
Renewable energy forecasting is crucially important because of its fluctuation and stochastic characteristics. In this paper, a hybrid model for wind speed and power forecasting using neuro wavelet and long short-term...
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Ensuring trust in the semiconductor IC supply chain necessitates the critical detection of Hardware Trojans, yet current methods relying on side-channel analysis often require the use of golden chips for verification....
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This study aims to analyse, control, and observe the Quarter Car Suspension System Model using Simulink. We begin by simplifying the system to a 1-D multiple spring-damper configuration and constructing its state-spac...
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This paper models both analytically and using finite element analysis (FEA), a prevalent mechanical fault in wound rotor induction motors (WRIMs). Variations in air gap length axially and circumferentially result in i...
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Nowadays, skin diseases are very common due to increasing bacterial attack, fungal infection, UVB rays due to the depleting ozone layer. So, if we can take preventive measures from early on, then we can increase the r...
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