Twice Gaussian mutation controlled the algorithm process. Inertia weight was adjusted dynamically.

该算法通过两次高斯变异控制算法进程，同时动态调节惯性权重。

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The Elitist model is utilized to ensure the stable convergence, and the Gaussian mutation operator is used to enhance the local search ability around every peak value.

采用最优保存策略和高斯变异算子，保证算法的稳定收敛和提高算法在每个峰值附近的局部搜索能力。

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The Elitist model is utilized to ensure the stable convergence, and the Gaussian mutation operator is used to enhance the local search ability around every peak value.

采用最优保存策略和高斯变异算子，保证算法的稳定收敛和提高算法在每个峰值附近的局部搜索能力。

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