Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
code optimization » codon optimization (Expand Search), model optimization (Expand Search), dose optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
code optimization » codon optimization (Expand Search), model optimization (Expand Search), dose optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
lines based » lens based (Expand Search), genes based (Expand Search), lines used (Expand Search)
data code » data model (Expand Search), data came (Expand Search)
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Sensitivity and Specificity Analysis.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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68
CSI, Balanced accuracy, and FMI Analysis.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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69
Architecture of CDL Network.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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70
Hyper-parameter tuning of the proposed model.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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71
Accuracy and F-Measure Analysis.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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72
FPR and FNR analysis.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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73
Comparative Analysis of Mitosis Detection Method.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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74
Markedness and NLR Analysis.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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75
Accuracy vs loss for varying epochs.
Published 2025“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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76
Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential
Published 2023“…In this study, we systematically studied the energy distribution of bioactive conformations of small molecular ligands in their conformational ensembles using ANI-2X, a machine learning potential, in conjunction with one of our recently developed geometry optimization algorithms, known as a conjugate gradient with backtracking line search (CG-BS). …”
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77
Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential
Published 2023“…In this study, we systematically studied the energy distribution of bioactive conformations of small molecular ligands in their conformational ensembles using ANI-2X, a machine learning potential, in conjunction with one of our recently developed geometry optimization algorithms, known as a conjugate gradient with backtracking line search (CG-BS). …”
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78
Flowchart of PRGA algorithm.
Published 2025“…A case study of a bidirectional disruption during the 08:00–10:00 on the section of Xi’an Metro Line 2 demonstrates that: (1) The proposed model exhibits stronger robustness under demand uncertainty, achieving a reduction of 3 dispatched vehicles and a cost saving of 9,439 RMB by moderately increasing passenger costs by 850 RMB and extending bridging time; (2) The RPGA algorithm outperforms Non-dominated Sorting Genetic Algorithm II (NSGA-II), Reinforcement Learning-based NSGA-II (RLNSGA-II), and Multi-objective Particle Swarm Optimization Algorithm (MOPSO) in hypervolume (HV), generational distance (GD), and non-dominated ratio (NDR); (3) Increasing the rated passenger capacity within a certain range can reduce average passenger delays but correspondingly raises transportation costs. …”
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