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1_decoding algorithm » modeling algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
image 1_decoding » image 1_developing (Expand Search), table 1_decoding (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
1_decoding algorithm » modeling algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
image 1_decoding » image 1_developing (Expand Search), table 1_decoding (Expand Search)
data algorithm » data algorithms (Expand Search), update algorithm (Expand Search), atlas algorithm (Expand Search)
element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
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Algorithmic experimental parameter design.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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Spatial spectrum estimation for three algorithms.
Published 2024“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”
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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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Performance of the machine learning algorithms.
Published 2025“…We developed and interpreted machine-learning (ML) models to predict hypertension and rank associated factors among married women with the goal of informing targeted screening and policy in low-resource settings.…”
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Performance of the machine learning algorithms.
Published 2025“…We developed and interpreted machine-learning (ML) models to predict hypertension and rank associated factors among married women with the goal of informing targeted screening and policy in low-resource settings.…”
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Optimal parameters of the machine learning algorithm.
Published 2025“…<p>Optimal parameters of the machine learning algorithm.</p>…”