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A Genetic-Based Fuzzy Clustering Algorithm for Fault Diagnosis in Satellite Attitude Determination System

机译:一种基于遗传态诊断卫星姿态确定系统的基于遗传模糊聚类算法

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The paper presents a genetic-based fuzzy clustering algorithm for fault diagnosis in satellite attitude determination system (ADS). The traditional fuzzy c-means(FCM) algorithm is local search techniques that search for the optimum by using a hill-climbing techniques. Thus, it often fail in the search for global optimum. Genetic algorithm is a stochastic global optimization algorithm, their combination can prevent FCM being trapped in a local optimum and sensitive to the initializations. Simulation results show that the proposed approach have much higher probabilities of finding global optimal solutions than traditional FCM algorithm, and provide accurate clustering for fault mode
机译:本文提出了一种基于遗传的模糊聚类算法,用于卫星姿态确定系统(广告)中的故障诊断。传统的模糊C-Means(FCM)算法是通过使用爬山技术搜索最佳的本地搜索技术。因此,它经常在寻找全球最优的过程中失败。遗传算法是一种随机全局优化算法,它们的组合可以防止FCM被困在局部最佳和初始化的敏感。仿真结果表明,该方法比传统的FCM算法找到全球最佳解决方案的概率更高,并为故障模式提供准确的聚类

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