By means of fuzzy statistical methods, the discussion on fuzzy features of the system motion and the methods used to solve fuzzy equations is made.
从这两方面的因素着手，借助模糊统计方法，探讨系统运动的模糊性及模糊方程的求解方法。
The fuzzy relation equations based on inner transformation a re discussed.
研究一类基于内变换的模糊关系方程的解法。
By the parametric representation, fuzzy number means a bounded continuous curve in the two-dimensional metric space R2, so that it is easy to analyze fuzzy differential equations.
在此参数表示下，模糊数可直接视为二维度量空间r 2中的有界连续曲线，这给分析模糊微分方程带来了便利。
We transfer fuzzy system of nonlinear equations into a nonlinear programming. Then, some methods of nonlinear programming are used.
首先把模糊非线性方程组转变成非线性规划，再用非线性规划中的方法或软件来解。
Based on resolution of interval Numbers and fuzzy resolution theorem, we develop a method of solving the structural fuzzy finite element equilibrium equations.
利用区间数的分解和模糊分解定理，研究了一种结构模糊有限元平衡方程的求解方法。
The resolution problem of fuzzy relation equations (FRES) is a very important subject in fuzzy sets and systems, the majority of fuzzy inference systems can be implemented by using FERS.
模糊关系方程的求解问题是模糊集与系统中极其重要的研究课题之一，大部分模糊推理系统都可以通过模糊关系方程实现。
Several efficient methods for solving the static governing equations of fuzzy FEM were presented.
提出了区间变量的若干运算规则，和模糊有限元静力控制方程的求解方法。
A new kind of fuzzy time series model is presented by using a fuzzy system of linear equations with fuzzy coefficients and real variables.
利用模糊系数实变量的线性方程组建立了一种新的模糊随机时间序列模型。
Kalman filter of the kind of equations was calculated with T-SFIMMA algorithm based on adaptive Kalman filter algorithm of T-S fuzzy model, realize the tracking and automatic switchover of models.
对各方程序卡尔曼滤波，通过T -SFIMMA算法进行基于T - S模糊模型的自适应卡尔曼滤波计算，实现系统模型的实时跟踪与自动转换。
According to the membership function of parameters, the equations of fuzzy eigenvalue of sample parameters was deduced.
在确定的参数隶属函数基础上，推导了岩土样本力学参数模糊统计特征值的计算公式。
The fuzzy and stochastic features a moored floating body system are described in order to deduce its fuzzy motion equations.
对系泊浮体系统的模糊随机性特征进行描述，并推导其模糊运动方程。
The T-S model is used to extend the fully-decoupled parity equations to fuzzy parity equations for nonlinear systems.
引入T-S模型将全解耦奇偶方程推广到非线性系统中得到了模糊奇偶方程。
The proposed fuzzy clustering algorithm incorporates the discriminating vector into its update equations such that the obtained update equations do not take commonly-used FCM-like forms.
该算法将鉴别矢量引入迭代更新方程，因此其异于常见的FCM聚类方程形式。
The proposed fuzzy clustering algorithm incorporates the discriminating vector into its update equations such that the obtained update equations do not take commonly-used FCM-like forms.
该算法将鉴别矢量引入迭代更新方程，因此其异于常见的FCM聚类方程形式。
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