通过定义相对适应度(relative fitness),单种群进化算法是可以解决这类问题的(MitcheU and Forrest,1994),但 是效率不尽人意,容易陷入进化停滞的状态。
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By constructing two mutual competitive populations, the algorithm produces the optimal individual in a bootstrapping process using relative fitness criteria instead of absolute fitness criteria.
通过构建2个相互竞争的种群,采用相对适应度度量方法,在一个纯自举的过程中产生最优竞争个体。
参考来源 - 基于粒子群优化和遗传算法的协同聚类算法·2,447,543篇论文数据,部分数据来源于NoteExpress
同时,设计了基于影响度因子的相对适应度函数来消除目标非标准化误差。
At the same time, relative fitness which was based on influence degree coefficient was designed to reduce objects' non-standardization error.
相对残差产生器的主动鲁棒性设计,自适应阈值方法也是提高故障检测系统的灵敏度和鲁棒性的一种有效方法。
Compared with active robust approaches based on generating residuals, robustness and sensitivity of fault detection system can be enhanced by using adaptive thresholds too.
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