بدائل البحث:
source optimization » resource optimization (توسيع البحث), surface optimization (توسيع البحث), source utilization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data source » data sources (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
source optimization » resource optimization (توسيع البحث), surface optimization (توسيع البحث), source utilization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
primary data » primary care (توسيع البحث)
data source » data sources (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
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21
Pseudo Code of RBMO.
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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22
P-value on CEC-2017(Dim = 30).
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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23
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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24
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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25
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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26
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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27
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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28
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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29
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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30
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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32
Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation.
منشور في 2022"…<b>(C)</b> Schematic of the proposed algorithm. a) Real data from a source domain is translated by the generator to resemble data from a specified target domain while maintaining underlying semantic qualities of the input image. b) Translated data is reconstructed by the generator to resemble data from the source domain to maintain domain-agnostic image characteristics with a semantic consistency constraint ensuring that reconstructed images maintain the semantic characteristics of the source data. c) The discriminator aims to distinguish between real and synthetic images and identify the domain of input images to constrain the generator to produce realistic-looking synthetic images from a specified domain. d) A target discriminator is fine-tuned on synthetic images to better identify opacity in the target domain.…"
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33
Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr">For more information about the data, one may refer to the article below:</p><p dir="ltr">Aref S, Ng B (2025) Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks. …"
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35
ECE6379_PSOM.zip
منشور في 2021"…Optimization algorithms that are commonly used to solve these problems will also be covered including linear programming, mixed-integer linear programming, Lagrange relaxation, dynamic programming, branch and bound, and duality theory.…"
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36
Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
منشور في 2022"…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"
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37
Sample image for illustration.
منشور في 2024"…<div><p>Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
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38
Comparison analysis of computation time.
منشور في 2024"…<div><p>Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
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39
Process flow diagram of CBFD.
منشور في 2024"…<div><p>Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
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40
Precision recall curve.
منشور في 2024"…<div><p>Feature description is a critical task in Augmented Reality Tracking. This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"