A new hybrid algorithm based on optimal fuzzy controller in multimachine power system

In this article, a new methodology based on fuzzy proportional‐integral‐derivative (PID) controller is proposed to damp low frequency oscillation in multimachine power system where the parameters of proposed controller are optimized offline automatically by hybrid genetic algorithm (GA) and particle swarm optimization (PSO) techniques. This newly proposed method is more efficient because it cope with oscillations and different operating points. In this strategy, the controller is tuned online from the knowledge base and fuzzy interference. In the proposed method, for achieving the desired level of robust performance exact tuning of rule base and membership functions (MF) are very important. The motivation for using the GA and PSO as a hybrid method are to reduce fuzzy effort and take large parametric uncertainties in to account. This newly developed control strategy mixed the advantage of GA and PSO techniques to optimally tune the rule base and MF parameters of fuzzy controller that leads to a flexible controller with simple structure while is easy to implement. The proposed method is tested on three machine nine buses and 16 machine power systems with different operating conditions in present of disturbance and nonlinearity. The effectiveness of proposed controller is compared with robust PSS that tune using PSO and the fuzzy controller which is optimized rule base by GA through figure of demerit and integral of the time multiplied absolute value of the error performance indices. The results evaluation shows that the proposed method achieves good robust performance for a wide range of load change in the presents of disturbance and system nonlinearities and is superior to the other controllers. © 2014 Wiley Periodicals, Inc. Complexity 21: 78–93, 2015     

模糊故障诊断隶属函数的选择分析比较

讨论基于模糊规则的模糊诊断方法中隶属函数的选择问题，以同步电机的匝间线圈故障检测为例，将逆电流和逆电压作为模糊故障检测的两个输入变量，以同步电机的故障代码值为输出变量，分别采用三角形、梯形和高斯型三种隶属函数进行模拟，从模拟结果分析得出在一般电气设备的模糊故障诊断中，采用三角形隶属函数进行模糊故障诊断的准确度优于使用梯形和高斯形隶属度函数。     

带有模糊信息的多目标决策问题的改进灰模糊算法

将模糊数学和灰色理论结合在一起 ,针对目前复杂大系统的多目标决策问题 ,提出了一个简单实用而且有效的灰模糊求解方法 ,通过隶属函数的一致性使确定型指标和模糊型指标能融合在同一个决策中加以考虑 ,同时又介绍了一种与隶属度相关的确定权重的灰模糊方法     

A measure-theoretic axiomatization of fuzzy sets

Using measurement theory, this paper examines three empirical structures that underlie the representation of fuzzy sets: the fuzzy membership structure, the fuzzy component structure, and the fuzzy system structure. These qualitative structures justify the use of the standard min-max system to represent fuzzy sets. The results of this study facilitate the development of a sound measurement-theoretic axiomatization of fuzzy systems.     

基于最大隶属度原则的彩色图像分割方法

提出一种基于模糊最大隶属度原则的彩色图像分割方法.从彩色图像的彩色直方图中获取目标色和背景色，建立一组色彩模糊集，计算该图像中的色彩在各模糊集中的隶属度，并基于最大隶属度原则确定色彩的归属.基于上述最大隶属度的模糊模式识别原则建立了最大隶属度-径向基函数神经网络，实现了快速有效的彩色图像分割. 关键词： 最大隶属度原则 彩色图像分割 彩色直方图 神经网络     

区间模糊ISODATA动态聚类算法

目前模糊技术已经应用于许多智能系统,如模糊关系与模糊聚类.聚类是数据挖掘的重要任务,它将数据对像分成多个聚类,在同一个聚类中,对象的属性特征之间具有较高的相似度,有很大研究及应用价值.结合数据库中的挖掘技术,对属性特征为区间数的多属性决策问题,提出了一种基于区间数隶属度的区间模糊ISODATA动态聚类方法.     

Poverty Level of Households: A Multidimensional Approach Based on Fuzzy Mathematics

In recent years, extensive research jobs have been developed on the definition, measurement and analyzing of poverty. Poverty is a multidimensional phenomenon, thus a number of challenges appears measuring it. The fuzzy set theoretic approach has been used to measure the poverty and to classify the difference between poor and non-poor households. This paper aims at proposing a new methodology to measure the poverty index in fuzzy environment via a two-step membership function. The concept of one poverty line is chalked out first and then a general method is developed to split the poverty index. Linguistic variables are used for the attributes to find the membership values of the households against the attributes and to grade the attributes. The effectiveness and usefulness of the proposed method is numerically illustrated through a case study for rural household people living in remote rural areas of India.     

求解多层线性规划的模糊规划法

本文用模糊集理论中的隶属函数描述多层线性规划的各层目标,在第一层给定最小满意水平下,通过求解相应层次的模糊规划来确定各层的最小满意度,从而最终得到问题的一个满意解。提出的方法只需求解一系列线性规划问题,具有较好的计算复杂性和可行性,最后的算例进一步验证了方法的有效性。     

基于可变模糊集理论的城市用地适用性评估

依据可变模糊集理论,构造了城市用地适用性评估的相对差异函数模型和相对隶属函数模型,建立了求解综合相对隶属度的可变模糊评估模型,并应用该模型对2组待开发利用用地适用性进行了评估.研究表明:可变模糊评估是依据对立相对隶属函数来描述模糊概念,通过参数的可变性,自我验证可变模糊评估方法的可靠性,并通过级别特征值表达了评估对象属于某级别的程度,使评估结果更为精细,从而为城市用地适用性评估提供了一种有效的新方法.