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based optimization » whale optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), _ optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data path » data data (Expand Search), data part (Expand Search)
based optimization » whale optimization (Expand Search)
path optimization » swarm optimization (Expand Search), whale optimization (Expand Search), _ optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data path » data data (Expand Search), data part (Expand Search)
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. …”
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The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
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<i>hi</i>PRS algorithm process flow.
Published 2023“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …”
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Pseudo Code of RBMO.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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11
P-value on CEC-2017(Dim = 30).
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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12
Memory storage behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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13
Elite search behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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14
Description of the datasets.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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15
S and V shaped transfer functions.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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S- and V-Type transfer function diagrams.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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17
Collaborative hunting behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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18
Friedman average rank sum test results.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. variant comparison adaptation data.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
Published 2022“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”