بدائل البحث:
promotes classification » proposed classification (توسيع البحث), protein classification (توسيع البحث), producer classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
complex promotes » complex processes (توسيع البحث), complex process (توسيع البحث), complex problems (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
promotes classification » proposed classification (توسيع البحث), protein classification (توسيع البحث), producer classification (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
complex promotes » complex processes (توسيع البحث), complex process (توسيع البحث), complex problems (توسيع البحث)
binary complex » ternary complex (توسيع البحث), snare complex (توسيع البحث)
binary b » binary _ (توسيع البحث)
b based » _ based (توسيع البحث), 1 based (توسيع البحث), 2 based (توسيع البحث)
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41
Memory storage behavior.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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42
Elite search behavior.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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43
Description of the datasets.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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44
S and V shaped transfer functions.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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45
S- and V-Type transfer function diagrams.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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46
Collaborative hunting behavior.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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47
Friedman average rank sum test results.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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48
IRBMO vs. variant comparison adaptation data.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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49
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50
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51
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52
Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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53
Models and Dataset
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …"
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54
Supplementary Material 8
منشور في 2025"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"
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55
Flow diagram of the automatic animal detection and background reconstruction.
منشور في 2020"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"
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56
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"