Search alternatives:
features optimization » feature optimization (Expand Search), mixture optimization (Expand Search), resource optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
many features » main features (Expand Search), image features (Expand Search), key features (Expand Search)
binary many » binary mask (Expand Search), binary image (Expand Search)
binary task » binary mask (Expand Search)
task design » based design (Expand Search)
features optimization » feature optimization (Expand Search), mixture optimization (Expand Search), resource optimization (Expand Search)
design optimization » bayesian optimization (Expand Search)
many features » main features (Expand Search), image features (Expand Search), key features (Expand Search)
binary many » binary mask (Expand Search), binary image (Expand Search)
binary task » binary mask (Expand Search)
task design » based design (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
-
7
-
8
Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms.
Published 2025Subjects: -
9
Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm.
Published 2025Subjects: -
10
Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm.
Published 2025Subjects: -
11
-
12
-
13
-
14
Proposed Algorithm.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
-
15
The Pseudo-Code of the IRBMO Algorithm.
Published 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. …”
-
16
-
17
Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm.
Published 2025Subjects: -
18
Comparisons between ADAM and NADAM optimizers.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”
-
19
IRBMO vs. meta-heuristic algorithms boxplot.
Published 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. …”
-
20
IRBMO vs. feature selection algorithm boxplot.
Published 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. …”