本文通过改进模糊聚类方法确定模糊模型的前件结构，然后对经模糊聚类得到的模糊前件推理矩阵进行QR分解。
In the paper, the premise structure of fuzzy model is obtained by the improved fuzzy clustering. Fuzzy inference matrices are decomposed on the basis of QR decomposition.
针对概念衍生矩阵方法，给出该方法所需知识的框架表达形式，以及相应的概念推理机制。
In allusion to idea generation matrix, represents the knowledge included in the method based on frame, and proposes a correspondent mechanism of concept reasoning.
此外，还开发了用以形成模糊专家系统框架核心的推理机制，并通过线性模糊矩阵代数运算予以实现。
Moreover, a fuzzy inference mechanism was developed to form the core of fuzzy expert system frame, which could be realized through linear fuzzy matrix algebra.
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