Search alternatives:
bayesian optimization » based optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
sample bayesian » applied bayesian (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
bayesian optimization » based optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
sample bayesian » applied bayesian (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Bayesian network for BMV_OD model.
Published 2024“…Subsequently, Bayesian Network (BN) structure learning algorithms were utilized to construct 32 BN models after pairing the accident data from the four accident cluster types before and after sampling. …”
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Bayesian network for BMV_C1 model.
Published 2024“…Subsequently, Bayesian Network (BN) structure learning algorithms were utilized to construct 32 BN models after pairing the accident data from the four accident cluster types before and after sampling. …”
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Bayesian network for BMV_C3 model.
Published 2024“…Subsequently, Bayesian Network (BN) structure learning algorithms were utilized to construct 32 BN models after pairing the accident data from the four accident cluster types before and after sampling. …”
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Bayesian network for BMV_C2 model.
Published 2024“…Subsequently, Bayesian Network (BN) structure learning algorithms were utilized to construct 32 BN models after pairing the accident data from the four accident cluster types before and after sampling. …”
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The flowchart of the proposed algorithm.
Published 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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Results of network meta-analysis.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Results of network meta-analysis.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Results of network meta-analysis.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Results of network meta-analysis.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Study flowchart.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Risk of bias graph.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Results of network meta-analysis.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Characteristics of included studies.
Published 2023“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. …”
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Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation
Published 2024“…Originally introduced in the Bayesian imaging literature, ProxMCMC employs the Moreau-Yosida envelope for a smooth approximation of the total-variation regularization term, fixes variance and regularization strength parameters as constants, and uses the Langevin algorithm for the posterior sampling. …”
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Summary of literature review.
Published 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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Topic description.
Published 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. …”