بدائل البحث:
network optimization » swarm optimization (توسيع البحث), wolf optimization (توسيع البحث)
case optimization » based optimization (توسيع البحث), phase optimization (توسيع البحث), dose optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based case » base case (توسيع البحث), based cancer (توسيع البحث)
network optimization » swarm optimization (توسيع البحث), wolf optimization (توسيع البحث)
case optimization » based optimization (توسيع البحث), phase optimization (توسيع البحث), dose optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based case » base case (توسيع البحث), based cancer (توسيع البحث)
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61
Sample screening flowchart.
منشور في 2025"…Subsequently, a CI risk prediction model was constructed using four machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), and Logistic Regression (LR). …"
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62
Descriptive statistics for variables.
منشور في 2025"…Subsequently, a CI risk prediction model was constructed using four machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), and Logistic Regression (LR). …"
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63
SHAP summary plot.
منشور في 2025"…Subsequently, a CI risk prediction model was constructed using four machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), and Logistic Regression (LR). …"
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64
ROC curves for the test set of four models.
منشور في 2025"…Subsequently, a CI risk prediction model was constructed using four machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), and Logistic Regression (LR). …"
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65
Display of the web prediction interface.
منشور في 2025"…Subsequently, a CI risk prediction model was constructed using four machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), and Logistic Regression (LR). …"
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66
Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
منشور في 2019"…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …"
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67
Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
منشور في 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. …"
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68
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69
Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX
منشور في 2021"…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …"
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70
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73
Analysis and design of algorithms for the manufacturing process of integrated circuits
منشور في 2023"…From this, we propose: (i) a new ILP model, and (ii) a new solution representation, which, unlike the reference work, guarantees that feasible solutions are obtained throughout the generation of new individuals. Based on this new representation, we proposed and evaluated other approximate methods, including a greedy algorithm and a genetic algorithm that improve the state-of-the-art results for test cases usually used in the literature. …"
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74
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75
Testing results for classifying AD, MCI and NC.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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76
Summary of existing CNN models.
منشور في 2024"…<div><p>This study aims to develop an optimally performing convolutional neural network to classify Alzheimer’s disease into mild cognitive impairment, normal controls, or Alzheimer’s disease classes using a magnetic resonance imaging dataset. …"
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77
Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP
منشور في 2021"…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …"
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78
Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
منشور في 2025"…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …"
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80
Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"