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.
在建模的过程中将动态隶属度函数引入模糊预测推理方法，形成动态隶属度矩阵。
In the course of modeling, dynamic membership function is used in the fuzzy interval prediction, forming the matrix of dynamic membership function.
根据快速解耦潮流方程中系数矩阵是常数矩阵的特点，抽象出模糊命题，提出采用模糊推理的方法求解潮流问题。
In the fast decoupled load flow problem, the coefficient matrix is constant. According to this property, a fuzzy inference method is applied to solve the load flow problem.
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.
通过改进模糊聚类方法确定模糊模型的前件结构，并对模糊推理关系矩阵进行正交最小二乘估计。
The premise structure of fuzzy model is confirmed by the improved fuzzy clustering, and fuzzy relation matrix of fuzzy model is confirmed by orthogonal least square.
通过改进模糊聚类方法确定模糊模型的前件结构，并对模糊推理关系矩阵进行正交最小二乘估计。
The premise structure of fuzzy model is confirmed by the improved fuzzy clustering, and fuzzy relation matrix of fuzzy model is confirmed by orthogonal least square.
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