بدائل البحث:
structures generation » structure interaction (توسيع البحث), structural alteration (توسيع البحث), structure annotation (توسيع البحث)
generation algorithm » genetic algorithm (توسيع البحث), detection algorithm (توسيع البحث), selection algorithm (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
structures generation » structure interaction (توسيع البحث), structural alteration (توسيع البحث), structure annotation (توسيع البحث)
generation algorithm » genetic algorithm (توسيع البحث), detection algorithm (توسيع البحث), selection algorithm (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
-
1
-
2
Proposed Algorithm.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
3
Comparisons between ADAM and NADAM optimizers.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
4
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. …"
-
5
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. …"
-
6
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. …"
-
7
BCN-M: A Free Computational Tool for Generating Wulff-like Nanoparticle Models with Controlled Stoichiometry
منشور في 2019"…The bulk cut nanoparticle model (BCN-M) computational tool generates Wulff-like models for binary materials with controlled stoichiometry automatically with none or little need for further manipulation from the user. …"
-
8
An Example of a WPT-MEC Network.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
9
Related Work Summary.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
10
Simulation parameters.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
11
Training losses for N = 10.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
12
Normalized computation rate for N = 10.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
13
Summary of Notations Used in this paper.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
14
-
15
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. …"
-
16
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. …"
-
17
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. …"
-
18
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. …"
-
19
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. …"
-
20
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. …"