بدائل البحث:
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary from » diary from (توسيع البحث), library from (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
data process » data processing (توسيع البحث), damage process (توسيع البحث), data access (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
binary from » diary from (توسيع البحث), library from (توسيع البحث)
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81
Normalized computation rate for N = 10.
منشور في 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. …"
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82
Summary of Notations Used in this paper.
منشور في 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. …"
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83
Classification baseline performance.
منشور في 2025"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"
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84
Feature selection results.
منشور في 2025"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"
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85
ANOVA test result.
منشور في 2025"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"
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86
Summary of literature review.
منشور في 2025"…These findings highlight the potential of metaheuristic optimization techniques to improve the effectiveness of deep learning models in clinical diagnostics quantifiably. …"
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87
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88
Thesis-RAMIS-Figs_Slides
منشور في 2024"…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.…"
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89
DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf
منشور في 2022"…Optimized models were used to identify S. pneumoniae from other streptococci in an independent, previously unknown data set of 28 patient isolates. …"
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90
SHAP bar plot.
منشور في 2025"…</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…"
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91
Sample screening flowchart.
منشور في 2025"…</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…"
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92
Descriptive statistics for variables.
منشور في 2025"…</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…"
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93
SHAP summary plot.
منشور في 2025"…</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…"
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94
Display of the web prediction interface.
منشور في 2025"…</p><p>Objective</p><p>This study aimed to develop a risk prediction model for CI in CKD patients using machine learning algorithms, with the objective of enhancing risk prediction accuracy and facilitating early intervention.…"
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95
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96
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97
Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
منشور في 2021"…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …"
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98
Summary of literature review.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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99
Topic description.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"
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100
Notations along with their descriptions.
منشور في 2024"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"