Sugeno型模糊复集值积分在分类器融合中的应用探析

Application of Complex Sugeno Type Fuzzy Set-valued Integrals in Classifier Fusion Method

提出Sugeno型模糊复集值积分概念,概括其基本性质,以Sugeno型模糊复集值积分为工具,重点研究在分类器融合中应用的细节问题,并以2个具体实例给出操作实施步骤进行。结果显示:这种Sugeno型模糊复集值积分融合算法具有明显的优越性,采用双向隶属评价和模糊推理方法来进行案例最终分类,体现了分类的客观性、全面性,达到分类的较佳效果。

This paper presents the concept of complex Sugeno fuzzy set-valued integrals and reviews its basic properties.We discuss specific details of applying complex Sugeno type fuzzy set-valued integrals in classifier fusion,and we put the operational steps into practice through two examples, through bidirectional membership evaluation and fuzzy inference method.The final classification result reflects the objectivity and comprehensiveness.The results of this study demonstrate that the complex Sugeno fuzzy set-valued integral fusion algorithm is clearly superior to other existing methods.