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process optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
primary data » primary care (Expand Search)
data based » data used (Expand Search)
process optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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data based » data used (Expand Search)
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81
Table_4_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx
Published 2022“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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82
Table_2_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx
Published 2022“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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83
Table_6_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx
Published 2022“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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84
Table_10_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx
Published 2022“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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85
Table_3_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx
Published 2022“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”
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86
Models’ performance without optimization.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
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87
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RNN performance comparison with/out optimization.
Published 2024“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”
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89
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90
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91
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92
An Example of a WPT-MEC Network.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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93
Related Work Summary.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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94
Simulation parameters.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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95
Training losses for N = 10.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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96
Normalized computation rate for N = 10.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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97
Summary of Notations Used in this paper.
Published 2025“…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …”
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98
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100
A portfolio selection model based on the knapsack problem under uncertainty
Published 2019“…The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. Finally, a discrete firefly algorithm is designed to find the near optional solutions in large dimensions. …”