Search alternatives:
based optimization » whale optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
library based » laboratory based (Expand Search)
binary task » binary mask (Expand Search)
task based » risk based (Expand Search)
based optimization » whale optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
library based » laboratory based (Expand Search)
binary task » binary mask (Expand Search)
task based » risk based (Expand Search)
-
1
-
2
Proposed Algorithm.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
-
3
-
4
-
5
An optimal solution for the HFS instance.
Published 2025“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
-
6
Comparisons between ADAM and NADAM optimizers.
Published 2025“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
-
7
-
8
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. 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. …”
-
9
ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design
Published 2023“…Individual ligands from mononuclear crystal structures were identified using a modified depth-first search algorithm and charge was assigned using a machine learning model based on quantum-chemical calculated features. …”
-
10
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. 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
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. 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. …”
-
12
-
13
-
14
Comparison based on hard instances from [79].
Published 2025“…Finally, based on a large number of instances and real cases, IPMMPO-CP is compared with 9 representative algorithms and 2 latest CP models. …”
-
15
-
16
Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
Published 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. …”
-
17
-
18
-
19
-
20