IEEE CEC 2017 benchmark function specifications. حسب Kankan Tang (21474968)

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Comparison results on the Diabetes dataset. حسب Kankan Tang (21474968)

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IEEE CEC 2022 benchmark function specifications. حسب Kankan Tang (21474968)

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Evolutionary trajectory of OMWOA on the IEEE CEC 2017 benchmark functions. حسب Kankan Tang (21474968)

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Performance comparisons of OMWOA with state-of-the-art competitors on the IEEE CEC 2022 benchmark functions. حسب Kankan Tang (21474968)

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Scalability analysis on the IEEE CEC 2017 benchmark functions. حسب Kankan Tang (21474968)

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Scalability tests in three dimensions. حسب Kankan Tang (21474968)

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Comparison results on the Cleveland heart dataset. حسب Kankan Tang (21474968)

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Comparison results on the Bupa liver dataset. حسب Kankan Tang (21474968)

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Comparison results on the Breast cancer dataset. حسب Kankan Tang (21474968)

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Comparison results on the heart dataset. حسب Kankan Tang (21474968)

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Performance comparisons of OMWOA with state-of-the-art competitors on the IEEE CEC 2017. حسب Kankan Tang (21474968)

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Comparison results on the Heart dataset. حسب Kankan Tang (21474968)

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Comparison results on the Bupa liver dataset. حسب Kankan Tang (21474968)

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Comparison results on the Cleveland heart dataset. حسب Kankan Tang (21474968)

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Ablation analysis. حسب Kankan Tang (21474968)

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Comparison results on the Diabetes dataset. حسب Kankan Tang (21474968)

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Comparison results on the Breast Cancer dataset. حسب Kankan Tang (21474968)

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Various WOAs with three strategies. حسب Kankan Tang (21474968)

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Operational mechanism diagram of deep reinforcement learning retrieval optimization module, based on the user interaction retrieval strategy optimization process, encodes the user query vector, historical interaction record and knowledge graph subgraph representation into state space, designs reward function, and trains the policy network through the proximal policy optimization algorithm (PPO) to optimize the retrieval strategy. حسب Yali Chen (24494)

"…<p>Operational mechanism diagram of deep reinforcement learning retrieval optimization module, based on the user interaction retrieval strategy optimization process, encodes the user query vector, historical interaction record and knowledge graph subgraph representation into state space, designs reward function, and trains the policy network through the proximal policy optimization algorithm (PPO) to optimize the retrieval strategy.…"