بدائل البحث:
action optimization » reaction optimization (توسيع البحث), function optimization (توسيع البحث), codon optimization (توسيع البحث)
search optimization » swarm optimization (توسيع البحث), lead optimization (توسيع البحث), path optimization (توسيع البحث)
based action » based motion (توسيع البحث), based active (توسيع البحث), based fusion (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based search » based research (توسيع البحث)
action optimization » reaction optimization (توسيع البحث), function optimization (توسيع البحث), codon optimization (توسيع البحث)
search optimization » swarm optimization (توسيع البحث), lead optimization (توسيع البحث), path optimization (توسيع البحث)
based action » based motion (توسيع البحث), based active (توسيع البحث), based fusion (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based search » based research (توسيع البحث)
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Parameter settings of the comparison algorithms.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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The Pseudo-Code of the IRBMO Algorithm.
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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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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IRBMO vs. meta-heuristic algorithms boxplot.
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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IRBMO vs. feature selection algorithm boxplot.
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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Comparison in terms of the sensitivity.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Parameter sensitivity of BIMGO.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Details of the medical datasets.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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The flowchart of IMGO.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Comparison in terms of the selected features.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Iterative chart of control factor.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Details of 23 basic benchmark functions.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Related researches.
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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S1 Dataset -
منشور في 2024"…Finally, a neighborhood search strategy is used for the optimal individuals to enhance the exploitation and convergence capabilities of the algorithm. …"
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Datasets and their properties.
منشور في 2023"…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Parameter settings.
منشور في 2023"…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"
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Raw Data for the Thesis: "<i>Enhancing RNAi-Based Pest Control through Effective Target Gene Selection and Optimal dsRNA Design</i>"
منشور في 2025"…</p><p><br></p><p dir="ltr">Chapter 4 introduces the dsRIP web platform (<a href="https://dsrip.uni-goettingen.de/" target="_blank">https://dsrip.uni-goettingen.de/</a>) for designing sequence-optimized dsRNA for RNAi-based pest control. In the experimental part, small interfering RNA (siRNA) features that were associated with RNAi efficacy in human cells were tested in <i>T. castaneum </i>by targeting an essential gene and measuring insecticidal efficacy. …"