بدائل البحث:
fitting algorithm » finding algorithm (توسيع البحث), filtering algorithm (توسيع البحث), twisting algorithm (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
elements method » element method (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), novel algorithm (توسيع البحث), modbo algorithm (توسيع البحث)
data fitting » data settings (توسيع البحث), data mining (توسيع البحث)
data code » data model (توسيع البحث), data came (توسيع البحث)
fitting algorithm » finding algorithm (توسيع البحث), filtering algorithm (توسيع البحث), twisting algorithm (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
elements method » element method (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), novel algorithm (توسيع البحث), modbo algorithm (توسيع البحث)
data fitting » data settings (توسيع البحث), data mining (توسيع البحث)
data code » data model (توسيع البحث), data came (توسيع البحث)
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The schematic diagram of the hierarchical clustering algorithm.
منشور في 2025الموضوعات: "…original multidimensional data…"
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Proportion of simulated data with improved likelihood from using multiple restarts (Algorithm 1).
منشور في 2025الموضوعات: "…routinely applicable algorithm…"
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Ricker seismic profile.
منشور في 2025"…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …"
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Noise reduction on testing sets from STEAD.
منشور في 2025"…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …"
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SNR comparison of real-field seismic profile.
منشور في 2025"…<div><p>Seismic noise separation and suppression is an important topic in seismic signal processing to improve the quality of seismic data recorded at monitoring stations. We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …"