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The buffered work-pool approach for search-tree based optimization algorithms
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …”
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A Low-Cost Closed-Loop Solar Tracking System Based on the Sun Position Algorithm
Published 2019“…In summary, even for a small-scale solar tracking system, the algorithm-based closed-loop dual-axis tracking system can increase overall system efficiency. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques
Published 2024“…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network
Published 2022“…Because the diagnosis of many neurological diseases is heavily reliant on clean EEG data, it is critical to eliminate motion artifacts from motion-corrupted EEG signals using reliable and robust algorithms. Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …”
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las...
Published 2020“…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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Lagrangian tracking in stochastic fields with application to an ensemble of velocity fields in the Red Sea
Published 2018“…Lagrangian tracking of passive tracers in a stochastic velocity field within a sequential ensemble data assimilation framework is challenging due to the exponential growth in the number of particles. …”
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A Novel Internal Model Control Scheme for Adaptive Tracking of Nonlinear Dynamic Plants
Published 2006“…The U-model utilizes only past data for plant modelling and standard root solving algorithm for control law formulation. …”
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Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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Combining and adapting software quality predictive models by genetic algorithms
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study
Published 2022“…The present study focuses on investigating the structural integrity of rail track sections of the high-speed railways using the Rayleigh waves generated and sensed using a fully non-contact optical Laser system. …”
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Determining the Factors Affecting the Boiling Heat Transfer Coefficient of Sintered Coated Porous Surfaces
Published 2021“…In this regard, two Bayesian optimization algorithms including Gaussian process regression (GPR) and gradient boosting regression trees (GBRT) are used for tuning the hyper-parameters (number of input and dense nodes, number of dense layers, activation function, batch size, Adam decay, and learning rate) of the deep neural network. …”
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Software defect prediction. (c2019)
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems
Published 2019“…The Nonnested Generalized Exemplars (NNGE) algorithm is one of the most accurate classification techniques that can work with such data of CPPS. …”
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Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies
Published 2017Get full text
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Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. This paper proposes an adaptive Multi-layer Neural Network (MLNN) Luenberger observer-based control for altitude and attitude tracking of a quadrotor UAV. …”