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Description: 基于粗糙模糊神经网络,最近的模糊神经网络的应用-based on rough fuzzy neural networks, fuzzy recent application of neural networks
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Size: 34648 |
Author: shaojie |
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Description: 基于zigbee的温度控制模块开发，通过它可以粗略的了解无线通信产片的开发流程
-based on the temperature control module development, it can rough understanding of wireless communications in the film development process
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Size: 178176 |
Author: 王国松 |
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Description: MATLAB编写的用于属性约简的程序,先运行ROUGH.MDF文件,再输入RED,就可得到约简后的规则.-MATLAB prepared for the attribute reduction procedures, first running ROUGH.MDF documents, admission RED, can be about the simple rules.
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Size: 1024 |
Author: liyinmin |
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Description: 基于粗糙模糊神经网络,最近的模糊神经网络的应用-based on rough fuzzy neural networks, fuzzy recent application of neural networks
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Size: 34816 |
Author: shaojie |
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Description: 经典的人脸识别算法.求相关的模糊粗糙集属性约简的MATLAB源程序.急!谢谢.-classic face recognition algorithm. For the fuzzy rough set reduction MATLAB source. Desperate! Thank you.
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Size: 251904 |
Author: zhoulifang |
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Description: 粗糙集属性约简算法程序和相应的学术文章,以及一些参考资料和学习网站-Rough Set Attribute Reduction Algorithm procedures and the corresponding academic article, as well as some reference and learning site
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Size: 368640 |
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Description: 本书首先介绍了MATLAB 语言的程序设计的基本内容，在此基础上系统介绍了各个应用数
学领域的问题求解，如基于MATLAB 的微积分问题、线性代数问题的计算机求解、积分变换和复变函数问题、非线性方程与最优化问题、常微分方程与偏微分方程问题、数据插值与函数逼近问题、概率论与数理统计问题的解析解和数值解法等。还介绍了较新的非传统方法如模糊逻辑与模糊推理、神经网络、遗传算法、小波分析、粗糙集及分数阶微积分学等领域。-The book begins with the introduction of the MATLAB programming language, the basic content, on the basis of the system introduced in all areas of applied mathematics problem solving, such as MATLAB-based calculus problems, linear algebra to solve computer problems, integral transforms and complex variable function problems, nonlinear equations and optimization problems, ordinary differential equations and partial differential equation problems, data interpolation and function approximation problem, Probability Theory and Mathematical Statistics Analytical Solution and Numerical Solution of such. Also introduce a relatively new non-traditional methods such as fuzzy logic and fuzzy reasoning, neural networks, genetic algorithms, wavelet analysis, rough sets and fractional calculus and other fields.
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Size: 797696 |
Author: gongyl |
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Description: 属性约简的matlab代码：实现了基于信息熵、模糊信息熵；这些算法可以同时处理离散变量和数值变量，无须离散化。-Attribute Reduction of matlab code: to achieve based on information entropy, fuzzy information entropy these algorithms can deal with discrete variables and numerical variables without discretization.
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Size: 1746944 |
Author: 石永威 |
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Description: 基于"pca+lda+粗糙集+模糊神经网络"的人脸识别程序,在matlab上可直接运行-Based on pca+ Lda+ Rough Set+ Fuzzy neural network face recognition procedures can be directly run matlab
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Size: 7773184 |
Author: luo_hongbin |
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Description: data reduction with fuzzy rough sets or fuzzy mutual information
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Size: 169984 |
Author: sam |
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Description: data reduction with fuzzy rough sets or fuzzy mutual information
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Size: 1024 |
Author: sam |
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Description: fuzzy rough sets or fuzzy mutual information
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Size: 1024 |
Author: sam |
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Description: （压缩包里一共有5个代码）
pca+lda+粗糙集+模糊神经网络
saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat
1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat
2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat
3.将disdata组成决策表(savers.m)，通过对disdata的条件属性进行约简，得到其一个约简，组成新的测试集rstest和训练集rsstudy存为imagersdata.mat
4.对rsstudy进行模糊神经网络训练(savecul.m)，对模糊神经网络的参数进行调整学习将其存入culdata.mat
5.用runfnn.m对rstest进行测试得到其识别率
savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.-pca+ lda+ Rough Set+ fuzzy neural network
saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat
Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat
2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat
3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat
4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat
5. Rstest used to test for runfnn.m by its recognition rate
cm.m is savem.m and minimum distance classifier on the training set and test set classificati
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Size: 2048 |
Author: dong |
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Description: 一种适用于模式分类的模糊粗隶属函数神经网络-One for pattern classification of fuzzy-rough membership function neural network
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Size: 244736 |
Author: sds |
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Description: sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper:
Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000.
rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset.
Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts. -sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper:
Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000.
rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset.
Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts.
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Size: 730112 |
Author: NH |
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Description: 粗糙集代码
data reduction with fuzzy rough sets or fuzzy mutual information
fuzzy preference rough set based feature evaluation and selection
-Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection
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Size: 38912 |
Author: gq |
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Description: 模糊聚类和粗糙集关于web聚类很好的文章-Fuzzy Clustering and Rough Set Clustering good article on the web
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Size: 5180416 |
Author: yuwang2003 |
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Description: 这是采用模糊粗糙集的方法处理图像的matlab代码-This is a fuzzy rough set approach to image matlab code
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Size: 11415552 |
Author: lindahua |
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Description: This contains matlab code for rough fuzzy svm.It is done purely in matlab and only for binary case
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Size: 14336 |
Author: kishore |
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Description: 智能机器人机械臂动态可靠性粗糙_模糊综合评价研究Intelligent robot arm dynamic reliability rough fuzzy comprehensive evaluation _-Intelligent robot arm dynamic reliability rough fuzzy comprehensive evaluation _
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Size: 56320 |
Author: heart112 |
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