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The Study of Mixed Fuzzy CBR Technique and Using in Valve System Intelligent Design System

机译:混合模糊CBR技术及其在阀门系统智能设计系统中的应用研究。

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In this paper, we propose a hybrid decision model using case-based reasoning augmented the fuzzy logic and k nearest neighbor (k-NN) methods for aided design engine. The mixed fuzzy k-NN (MFKNN) CBR scheme which has trapezoidal, linear, negative linear, Triangular and Gaussian fuzzy operator is designed to compute memberships of engine and to provide a more flexible and practical mechanism for acquiring and reusing the expert system's decision knowledge. These methods were implemented in the database application and expert system following the example of valve system. To get the designed case, the retrieved results were compared and analyzed by mixed fuzzy k-NN algorithm or k-NN algorithm in the CBR database. It proves the validity of mixed fuzzy k-NN algorithm and CBR design system is used successfully in engine design process.
机译:在本文中,我们提出了一种基于案例推理的混合决策模型,该模型增强了辅助设计引擎的模糊逻辑和k最近邻(k-NN)方法。具有梯形,线性,负线性,三角和高斯模糊算子的混合模糊k-NN(MFKNN)CBR方案旨在计算发动机的隶属度,并提供一种更灵活实用的机制来获取和重用专家系统的决策知识。按照阀门系统的示例,在数据库应用程序和专家系统中实现了这些方法。为了获得设计的案例,在CBR数据库中使用混合模糊k-NN算法或k-NN算法对检索结果进行了比较和分析。证明了混合模糊k-NN算法的有效性,CBR设计系统已成功应用于发动机设计过程中。

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