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Research on Attribute Discretization for One Airborne Radar Intelligence System Based on Improved FCM Clustering

机译:基于改进FCM聚类的机载雷达情报系统属性离散化研究

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To address the information loss problem in the process of discretizing continuous attributes for one airborne radar intelligence system, this paper proposes a discretization method based on the improved FCM(Fuzzy c-means) algorithm through an analysis of the existing attribute discretization methods. This method improves the original algorithm by introducing the fuzzy decision theory and the validity index which is based on the geometric structure of the dataset, and uses this method to make the continuous attributes fuzzy. It overcomes the shortcomings that the conventional fuzzy clustering method must use two prespecified parametersȁ4;the weighted index m and the number of clusters c, and does not consider the specified attribute values of the dataset. We use the proposed method to discretize the continuous attributes in the airborn radar intelligence database and experimental results show that the scheme is feasible and effective.
机译:针对一个机载雷达情报系统连续属性离散化过程中的信息丢失问题,通过对现有的属性离散化方法进行分析,提出了一种基于改进的FCM(Fuzzy c-means)算法的离散化方法。该方法通过引入模糊决策理论和基于数据集几何结构的有效性指标对原始算法进行了改进,并使用该方法使连续属性变得模糊。它克服了传统的模糊聚类方法必须使用两个预先指定的参数ȁ4的缺点;加权指标m和聚类数c,并且不考虑数据集的指定属性值。我们使用提出的方法离散化了机载雷达情报数据库中的连续属性,实验结果表明该方案是可行和有效的。

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