Search alternatives:
guided optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary task » binary mask (Expand Search)
primary aim » primary care (Expand Search), primary data (Expand Search)
aim based » ai based (Expand Search), bim based (Expand Search), aom based (Expand Search)
guided optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary task » binary mask (Expand Search)
primary aim » primary care (Expand Search), primary data (Expand Search)
aim based » ai based (Expand Search), bim based (Expand Search), aom based (Expand Search)
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1
Routing policy based on path satisfaction.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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2
Flowchart of simple ant colony algorithm.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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3
Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement
Published 2019“…The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. …”
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4
The Pseudo-Code of the IRBMO Algorithm.
Published 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. …”
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6
IRBMO vs. meta-heuristic algorithms boxplot.
Published 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. …”
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7
IRBMO vs. feature selection algorithm boxplot.
Published 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. …”
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8
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9
Business priorities.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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10
Topology of 14-node communication network.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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11
Changes of risk value under different parameters.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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12
Performance of active and standby paths.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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13
DATA.
Published 2025“…These enhancements aim to achieve optimal routing scheduling based on risk information. …”
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14
Fig 9 -
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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15
Predictive performance indicators.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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16
Fig 8 -
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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17
GBO procedure.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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18
LEO pseudocode.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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19
Boxplots in EV tests.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”
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20
GBO parameters for HEV.
Published 2023“…The GBO minimizes a cost with the aim of selecting the optimal candidate for updating the SOH through a memory-fading forgetting factor. …”