بدائل البحث:
data optimization » path optimization (توسيع البحث), dose optimization (توسيع البحث), art optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
genes based » gene based (توسيع البحث), lens based (توسيع البحث)
based swarm » based sars (توسيع البحث), based smart (توسيع البحث), based arm (توسيع البحث)
based data » used data (توسيع البحث)
data optimization » path optimization (توسيع البحث), dose optimization (توسيع البحث), art optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
genes based » gene based (توسيع البحث), lens based (توسيع البحث)
based swarm » based sars (توسيع البحث), based smart (توسيع البحث), based arm (توسيع البحث)
based data » used data (توسيع البحث)
-
1
-
2
-
3
-
4
-
5
Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"
-
6
Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
منشور في 2022"…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"
-
7
Proposed Algorithm.
منشور في 2025"…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. …"
-
8
Parameter settings of the comparison algorithms.
منشور في 2024"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"
-
9
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. …"
-
10
-
11
Comparisons between ADAM and NADAM optimizers.
منشور في 2025"…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. …"
-
12
-
13
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. …"
-
14
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. …"
-
15
Table1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.docx
منشور في 2024"…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …"
-
16
DataSheet1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.ZIP
منشور في 2024"…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …"
-
17
GSE96058 information.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
-
18
The performance of classifiers.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
-
19
-
20