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learning algorithm » learning algorithms (Expand Search)
backing algorithm » tracking algorithm (Expand Search), making algorithm (Expand Search), tracking algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
learning algorithm » learning algorithms (Expand Search)
backing algorithm » tracking algorithm (Expand Search), making algorithm (Expand Search), tracking algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
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Algorithmic experimental parameter design.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Spatial spectrum estimation for three algorithms.
Published 2024“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…This research presents Data-Driven Intrusion Detection System in Internet of Things utilizing Optimized Bayesian Regularization-Back Propagation Neural Network (DIDS-BRBPNN-BBWOA-IoT) to overcome these issues. …”
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Evaluating the Efficacy of Different Machine Learning Methods to Classify Cancer Data.
Published 2025Subjects: -
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Acceleration data of African white-backed vultures with behaviour labels
Published 2024“…<p dir="ltr">This dataset is part of the publication "Death detector: Using vultures as sentinels to detect carcasses by combining bio-logging and machine learning" and was used to train machine learning algorithms for behaviour classification.…”
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Types of machine learning algorithms.
Published 2024“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.</p><p>Materials and methods</p><p>This study used the latest nationally representative cross-sectional Bangladesh demographic health survey (BDHS), 2017–18 data. …”
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Table 1_Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development...
Published 2025“…Objective<p>This study utilized National Health and Nutrition Examination Survey (NHANES) data to investigate the associations between weight-adjusted waist index (WWI), body mass index (BMI), and chronic low back pain (CLBP) risk, and to develop machine learning models to assess the predictive capacity of WWI for CLBP.…”
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