بدائل البحث:
robust optimization » process optimization (توسيع البحث), robust estimation (توسيع البحث), joint optimization (توسيع البحث)
binary model » final model (توسيع البحث), injury model (توسيع البحث), tiny model (توسيع البحث)
model robust » model robustness (توسيع البحث)
swarm » warm (توسيع البحث)
robust optimization » process optimization (توسيع البحث), robust estimation (توسيع البحث), joint optimization (توسيع البحث)
binary model » final model (توسيع البحث), injury model (توسيع البحث), tiny model (توسيع البحث)
model robust » model robustness (توسيع البحث)
swarm » warm (توسيع البحث)
-
1
-
2
-
3
-
4
-
5
QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
منشور في 2020"…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"
-
6
The Pseudo-Code of the IRBMO Algorithm.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
7
IRBMO vs. meta-heuristic algorithms boxplot.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
8
IRBMO vs. feature selection algorithm boxplot.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
9
-
10
-
11
-
12
Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
منشور في 2021"…Both in silico design and data analysis descriptors and norm index were employed to encode the structural characteristics of binary IL mixtures. The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …"
-
13
-
14
Pseudo Code of RBMO.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
15
P-value on CEC-2017(Dim = 30).
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
16
Memory storage behavior.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
17
Elite search behavior.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
18
Description of the datasets.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
19
S and V shaped transfer functions.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"
-
20
S- and V-Type transfer function diagrams.
منشور في 2025"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"