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Cluster analysis for fuzzy control systems

机译:模糊控制系统的集群分析

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This paper focuses on fuzzy control of a class of adaptive information systems (AIS), which are characterized by model uncertainty and inequality model constraints. Classification of a priori knowledge and identification of new data are central in the fuzzy control process. Knowledge representation scheme has direct impact on the development, efficiency, speed and maintenance of any knowledge based system. The paper considers cluster analysis for such a system, based on Bezdek's fuzzy cluster method (FCM). The proposed method is used to classify the input data and to receive the rules for AIS. The obtained rules can than be used for the design of rule-based intelligent system.
机译:本文重点介绍了一类自适应信息系统(AIS)的模糊控制,其特征在于模型不确定性和不等式模型约束。先验知识和新数据识别的分类是模糊控制过程中的中心。知识代表方案对任何知识的系统的开发,效率,速度和维护有直接影响。根据Bezdek的模糊聚类方法(FCM),本文考虑了这种系统的集群分析。该方法用于对输入数据进行分类并接收AIS的规则。所获得的规则可能用于设计基于规则的智能系统。

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