蚁群算法是一种新型的模拟进化算法，它通过模拟蚁群在觅食过程中寻找最短路径的方法来求解优化问题。

Ant Colony optimization (ACO) is a new-style simulating evolution algorithm. The behavior of real ant colonies foraging for food is simulated and used for solving optimization problems.

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在连续潮流法的基础上，结合经过改进的差异进化算法，通过对变量的组合优化，求取系统静态电压稳定安全裕度。

By combining the continuous power flow method with improved differential evolution calculation, the static voltage stability margin is found via optimal grouping of relevant variables.

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根据免疫学研究中抗原与抗体同时进化的特性，通过对动目标预测系统特点的分析，提出一种改进的免疫算法。

Based on the property that antigen and antibody are evolving simultaneously in immunology, an improved immune algorithm is presented through analysis of moving object forecast system.

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