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element data » settlement data (Expand Search), relevant data (Expand Search), movement data (Expand Search)
data fitting » data settings (Expand Search), data mining (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
fitting algorithm » finding algorithm (Expand Search), filtering algorithm (Expand Search), twisting algorithm (Expand Search)
data processing » image processing (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)
data fitting » data settings (Expand Search), data mining (Expand Search)
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Ricker seismic profile.
Published 2025“…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.
Published 2025“…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.
Published 2025“…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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The flowchart of GWO-VMD method.
Published 2025“…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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The 147th single trace.
Published 2025“…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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data and code
Published 2025“…Combined with the road network data, this algorithm regards the trajectory data as a signal that changes dynamically with time, converts it from time domain to frequency domain through Fourier transform, fits the trajectory points in the spectrum domain, and converts the discrete trajectory points into time continuous line elements.…”
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<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
Published 2025“…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”