搜索资源列表
模糊c-均值算法是模糊聚类
- 模糊c-均值算法是模糊聚类中最常见、应用最广泛的分析方法之一．经典FCM算法理论和应用的研究已经相当成熟，Bezdek业已证明算法的收敛性［6］，许多软件提供了多种方便的FCM工具箱(如Matlab中FCM工具箱等)．但是传统FCM算法处理的是普通数据集，不能直接处理区间数，得到的聚类原型也不是区间数．针对区间数，一种直觉的方法是分别对左区间值和右区间值作FCM，并把得到的聚类原型分别作为区间型聚类原型的左右区间值，但这种方法已经被证明是行不通的［6］-fuzzy c-means cluster
fcs_tanker
- Fuzzy Control System for a Tanker Ship This program simulates a fuzzy control system for a tanker ship. It has a fuzzy controller with two inputs, the error in the ship heading (e) and the change in that error (c). The output of the fuzzy controlle
266
- This paper shows a proposal for Type-reduction of an Interval Type-2 fuzzy set composed from α-cuts done over its primary membership functions. The defi nition of available Type-reduction methods for Interval Type-2 fuzzy sets are based
matlab
- 证据理论中区间模糊matlab实现，用于决策推理-Interval fuzzy evidence theory matlab achieve for decision-making reasoning
ITERV2FUZZYLS
- This tutorial illustrates the basic ideas of interval type-2 (IT2) fuzzy sets and systems, and provides a Matlab implementation of IT2 fuzzy logic system (FLS). One obstacle in learning IT2 fuzzy logic is its complex notations. In this tutorial w
NWA-Folder
- This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M endel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEE
EIA
- This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M endel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEEE
fuzzy-type-2
- Fuzzy logic systems (FLSs) usually employ type-1 fuzzy sets and represent uncertainty by numbers in the range [0,1] which are referred to as degrees of membership. Type-2 fuzzy sets are an extension of type-1 fuzzy sets with an additional dim
Toolbox
- matlab codes for interval type-2 fuzzy
fuzzy c-means
- 基于fuzzy c-means（FCM）的无监督模糊聚类算法，输出值有：各个样本的类别标签、目标函数在每次迭代后的值、聚类中心以及聚类区间。内有测试数据data.mat，点击 test.m 可以完美运行。(The unsupervised fuzzy clustering algorithm based on fuzzy c-means (FCM) outputs the class labels of each sample, the value of the target function