بدائل البحث:
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
recent detection » event detection (توسيع البحث), defect detection (توسيع البحث), recent attention (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
element » elements (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
recent detection » event detection (توسيع البحث), defect detection (توسيع البحث), recent attention (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
element » elements (توسيع البحث)
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Algorithmic experimental parameter design.
منشور في 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.
منشور في 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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Scatter diagram of different principal elements.
منشور في 2025"…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …"
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Example of a HS being wrongly detected by the GRF threshold method due to foot-dragging.
منشور في 2025الموضوعات: -
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Cellwise Outlier Detection in Heterogeneous Populations
منشور في 2025"…In the model-based clustering literature, several methodologies have been proposed to detect units that deviate from the majority of the data (rowwise outliers) and trim them from the parameter estimates. …"
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