بدائل البحث:
features optimization » feature optimization (توسيع البحث), mixture optimization (توسيع البحث), resource optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
deep features » level features (توسيع البحث), key features (توسيع البحث), edge features (توسيع البحث)
primary deep » primary sleep (توسيع البحث), primary level (توسيع البحث), primary dates (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
features optimization » feature optimization (توسيع البحث), mixture optimization (توسيع البحث), resource optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
deep features » level features (توسيع البحث), key features (توسيع البحث), edge features (توسيع البحث)
primary deep » primary sleep (توسيع البحث), primary level (توسيع البحث), primary dates (توسيع البحث)
binary task » binary mask (توسيع البحث)
task based » risk based (توسيع البحث)
-
1
Features selected by optimization algorithms.
منشور في 2024"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …"
-
2
-
3
Hybrid feature selection algorithm of CSCO-ROA.
منشور في 2024"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …"
-
4
Proposed Algorithm.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
5
-
6
Comparisons between ADAM and NADAM optimizers.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
7
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. …"
-
8
-
9
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. …"
-
10
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. …"
-
11
-
12
An Example of a WPT-MEC Network.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
13
Related Work Summary.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
14
Simulation parameters.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
15
Training losses for N = 10.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
16
Normalized computation rate for N = 10.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
17
Summary of Notations Used in this paper.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
-
18
-
19
-
20
Proposed reinforcement learning architecture.
منشور في 2025"…Experimental evaluation were conducted employing Deep Q Networks (DQN) and Proximal Policy Optimization (PPO) algorithms within ViZDoom and Unity reinforcement learning environments. …"