期刊文献+
共找到278篇文章
< 1 2 14 >
每页显示 20 50 100
Multi-Granularity Neighborhood Fuzzy Rough Set Model on Two Universes
1
作者 Ju Wang Xinghu Ai Li Fu 《Journal of Intelligent Learning Systems and Applications》 2024年第2期91-106,共16页
The two universes multi-granularity fuzzy rough set model is an effective tool for handling uncertainty problems between two domains with the help of binary fuzzy relations. This article applies the idea of neighborho... The two universes multi-granularity fuzzy rough set model is an effective tool for handling uncertainty problems between two domains with the help of binary fuzzy relations. This article applies the idea of neighborhood rough sets to two universes multi-granularity fuzzy rough sets, and discusses the two-universes multi-granularity neighborhood fuzzy rough set model. Firstly, the upper and lower approximation operators are defined in the two universes multi-granularity neighborhood fuzzy rough set model. Secondly, the properties of the upper and lower approximation operators are discussed. Finally, the properties of the two universes multi-granularity neighborhood fuzzy rough set model are verified through case studies. 展开更多
关键词 fuzzy Set Two Universes Multi-Granularity Rough Set Multi-Granularity neighborhood fuzzy Rough Set
下载PDF
NL-fuzzy拓扑空间中的N-紧性
2
作者 王小霞 高佳欣 李乔乔 《沈阳大学学报(自然科学版)》 CAS 2024年第4期364-368,共5页
利用α-远域族定义了NL-fuzzy拓扑空间中的N-紧性,借助α-分子网,模糊滤子以及模糊滤子基的概念给出其等价刻画。证明了N-紧性具有拓扑不变性以及有限多个N-紧集的并仍为N-紧集等性质。
关键词 NL-fuzzy拓扑空间 α-远域族 N-紧性 模糊滤子 拓扑不变性
下载PDF
Pruned fuzzy K-nearest neighbor classifier for beat classification 被引量:2
3
作者 Muhammad Arif Muhammad Usman Akram Fayyaz-ul-Afsar Amir Minhas 《Journal of Biomedical Science and Engineering》 2010年第4期380-389,共10页
Arrhythmia beat classification is an active area of research in ECG based clinical decision support systems. In this paper, Pruned Fuzzy K-nearest neighbor (PFKNN) classifier is proposed to classify six types of beats... Arrhythmia beat classification is an active area of research in ECG based clinical decision support systems. In this paper, Pruned Fuzzy K-nearest neighbor (PFKNN) classifier is proposed to classify six types of beats present in the MIT-BIH Arrhythmia database. We have tested our classifier on ~ 103100 beats for six beat types present in the database. Fuzzy KNN (FKNN) can be implemented very easily but large number of training examples used for classification can be very time consuming and requires large storage space. Hence, we have proposed a time efficient Arif-Fayyaz pruning algorithm especially suitable for FKNN which can maintain good classification accuracy with appropriate retained ratio of training data. By using Arif-Fayyaz pruning algorithm with Fuzzy KNN, we have achieved a beat classification accuracy of 97% and geometric mean of sensitivity of 94.5% with only 19% of the total training examples. The accuracy and sensitivity is comparable to FKNN when all the training data is used. Principal Component Analysis is used to further reduce the dimension of feature space from eleven to six without compromising the accuracy and sensitivity. PFKNN was found to robust against noise present in the ECG data. 展开更多
关键词 ARRHYTHMIA ECG k-nearest NEIGHBOR PRUNING fuzzy Classification
下载PDF
Detection of Contamination Defect on Ice Cream Bar Based on Fuzzy Rule and Absolute Neighborhood 被引量:2
4
作者 LI Shaoli YUAN Weiqi 《Instrumentation》 2017年第3期24-34,共11页
The contamination proposed in this paper is a defect on the surface of ice cream bar,which is a serious security threat.So it is essential to detect this defect before launched on the market. A detection method of con... The contamination proposed in this paper is a defect on the surface of ice cream bar,which is a serious security threat.So it is essential to detect this defect before launched on the market. A detection method of contamination defect on the ice cream bar surface is proposed,which is based on fuzzy rule and absolute neighborhood feature. Firstly,the ice cream bar surface is divided into several sub-regions via the defined adjacent gray level clustering method. Then the alternative contamination regions are extracted from the sub-regions via the defined fuzzy rule. At last,the real contamination regions are recognized via the relationship between absolute neighborhood gray feature and default threshold. The algorithm was tested in the self-built image database SUT-D. The results show that the accuracy of the method proposed in this paper is 97.32 percent,which increases 2.68 percent at least comparing to the other typical algorithms. It indicates that the superiority proposed in this paper,which is of actual use value. 展开更多
关键词 fuzzy Rule Absolute neighborhood Icecream Bar CONTAMINATION Adjacent Dray Level Clustering
下载PDF
GHM-FKNN:a generalized Heronian mean based fuzzy k-nearest neighbor classifier for the stock trend prediction
5
作者 吴振峰 WANG Mengmeng +1 位作者 LAN Tian ZHANG Anyuan 《High Technology Letters》 EI CAS 2023年第2期122-129,共8页
Stock trend prediction is a challenging problem because it involves many variables.Aiming at the problem that some existing machine learning techniques, such as random forest(RF), probabilistic random forest(PRF), k-n... Stock trend prediction is a challenging problem because it involves many variables.Aiming at the problem that some existing machine learning techniques, such as random forest(RF), probabilistic random forest(PRF), k-nearest neighbor(KNN), and fuzzy KNN(FKNN), have difficulty in accurately predicting the stock trend(uptrend or downtrend) for a given date, a generalized Heronian mean(GHM) based FKNN predictor named GHM-FKNN was proposed.GHM-FKNN combines GHM aggregation function with the ideas of the classical FKNN approach.After evaluation, the comparison results elucidated that GHM-FKNN outperformed the other best existing methods RF, PRF, KNN and FKNN on independent test datasets corresponding to three stocks, namely AAPL, AMZN and NFLX.Compared with RF, PRF, KNN and FKNN, GHM-FKNN achieved the best performance with accuracy of 62.37% for AAPL, 58.25% for AMZN, and 64.10% for NFLX. 展开更多
关键词 stock trend prediction Heronian mean fuzzy k-nearest neighbor(FKNN)
下载PDF
Condition Monitoring of Roller Bearing by K-star Classifier andK-nearest Neighborhood Classifier Using Sound Signal
6
作者 Rahul Kumar Sharma V.Sugumaran +1 位作者 Hemantha Kumar M.Amarnath 《Structural Durability & Health Monitoring》 EI 2017年第1期1-17,共17页
Most of the machineries in small or large-scale industry have rotating elementsupported by bearings for rigid support and accurate movement. For proper functioning ofmachinery, condition monitoring of the bearing is v... Most of the machineries in small or large-scale industry have rotating elementsupported by bearings for rigid support and accurate movement. For proper functioning ofmachinery, condition monitoring of the bearing is very important. In present study soundsignal is used to continuously monitor bearing health as sound signals of rotatingmachineries carry dynamic information of components. There are numerous studies inliterature that are reporting superiority of vibration signal of bearing fault diagnosis.However, there are very few studies done using sound signal. The cost associated withcondition monitoring using sound signal (Microphone) is less than the cost of transducerused to acquire vibration signal (Accelerometer). This paper employs sound signal forcondition monitoring of roller bearing by K-star classifier and k-nearest neighborhoodclassifier. The statistical feature extraction is performed from acquired sound signals. Thentwo-layer feature selection is done using J48 decision tree algorithm and random treealgorithm. These selected features were classified using K-star classifier and k-nearestneighborhood classifier and parametric optimization is performed to achieve the maximumclassification accuracy. The classification results for both K-star classifier and k-nearestneighborhood classifier for condition monitoring of roller bearing using sound signals werecompared. 展开更多
关键词 K-star k-nearest neighborhood K-NN machine learning approach conditionmonitoring fault diagnosis roller bearing decision tree algorithm J-48 random treealgorithm decision making two-layer feature selection sound signal statistical features
下载PDF
弱L-fuzzy Hausdorff空间及其性质 被引量:13
7
作者 李尧龙 赵彬 《陕西师范大学学报(自然科学版)》 CAS CSCD 北大核心 2003年第2期16-19,共4页
研究了弱L fuzzyHausdorff空间的性质,包括L 好的推广、遗传性、可乘性、弱同胚不变性及其与其他分离性的关系.讨论了弱L fuzzyHaudorff空间范畴的性质,证明了弱L fuzzyHausdorff空间范畴是次T0拓扑空间范畴的满子范畴及弱L fuzzyHausdo... 研究了弱L fuzzyHausdorff空间的性质,包括L 好的推广、遗传性、可乘性、弱同胚不变性及其与其他分离性的关系.讨论了弱L fuzzyHaudorff空间范畴的性质,证明了弱L fuzzyHausdorff空间范畴是次T0拓扑空间范畴的满子范畴及弱L fuzzyHausdorff空间范畴是完备范畴. 展开更多
关键词 拓扑空间 弱L-fuzzy HAUSDORFF空间 范畴 遗传性 可乘性 弱同胚不变性 分离性
下载PDF
L-fuzzy的邻域算子、内部算子以及闭包算子之间的相互确定 被引量:5
8
作者 赵虎 钟晓静 李生刚 《陕西师范大学学报(自然科学版)》 CAS CSCD 北大核心 2010年第3期16-19,共4页
设X是集合,L是Hutton代数,FT(X,L)、FN(X,L)、FI(X,L)和FC(X,L)分别表示X上的L-fuzzy拓扑的全体、L-fuzzy邻域算子的全体、L-fuzzy内部算子的全体以及L-fuzzy闭包算子的全体.给出从FI(X,L)到FN(X,L)和FC(X,L)的一一对应φ32和φ34以及从... 设X是集合,L是Hutton代数,FT(X,L)、FN(X,L)、FI(X,L)和FC(X,L)分别表示X上的L-fuzzy拓扑的全体、L-fuzzy邻域算子的全体、L-fuzzy内部算子的全体以及L-fuzzy闭包算子的全体.给出从FI(X,L)到FN(X,L)和FC(X,L)的一一对应φ32和φ34以及从FN(X,L)到FC(X,L)的一一对应φ24,并且证明了可以在FT(X,L)、FN(X,L)、FI(X,L)以及FC(X,L)上定义适当的序关系,使得上述每个映射都是完备格同构. 展开更多
关键词 L-fuzzy拓扑 L-fuzzy邻域算子 L-fuzzy内部算子 L-fuzzy闭包算子 完备格同构
下载PDF
L-Fuzzy保序算子空间的ω-分离性 被引量:30
9
作者 黄朝霞 陈水利 《数学杂志》 CSCD 北大核心 2005年第4期383-388,共6页
在L-fuzzy保序算子空间中引进了ω-分离性等概念,系统地讨论了这些概念的性质,得出它们保持了L-fuzzy拓扑空间中的Ti分离性的主要结论,进而说明ω-分离性是R. Lowen的推广.
关键词 拓扑空间 L-fuzzy保序算子空间 ω-分离性 拓扑生成 远域
下载PDF
FUZZY WITHIN-CLASS MATRIX PRINCIPAL COMPONENT ANALYSIS AND ITS APPLICATION TO FACE RECOGNITION 被引量:3
10
作者 朱玉莲 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2008年第2期141-147,共7页
Matrix principal component analysis (MatPCA), as an effective feature extraction method, can deal with the matrix pattern and the vector pattern. However, like PCA, MatPCA does not use the class information of sampl... Matrix principal component analysis (MatPCA), as an effective feature extraction method, can deal with the matrix pattern and the vector pattern. However, like PCA, MatPCA does not use the class information of samples. As a result, the extracted features cannot provide enough useful information for distinguishing pat- tern from one another, and further resulting in degradation of classification performance. To fullly use class in- formation of samples, a novel method, called the fuzzy within-class MatPCA (F-WMatPCA)is proposed. F-WMatPCA utilizes the fuzzy K-nearest neighbor method(FKNN) to fuzzify the class membership degrees of a training sample and then performs fuzzy MatPCA within these patterns having the same class label. Due to more class information is used in feature extraction, F-WMatPCA can intuitively improve the classification perfor- mance. Experimental results in face databases and some benchmark datasets show that F-WMatPCA is effective and competitive than MatPCA. The experimental analysis on face image databases indicates that F-WMatPCA im- proves the recognition accuracy and is more stable and robust in performing classification than the existing method of fuzzy-based F-Fisherfaces. 展开更多
关键词 face recognition principal component analysis (PCA) matrix pattern PCA(MatPCA) fuzzy k-nearest neighbor(FKNN) fuzzy within-class MatPCA(F-WMatPCA)
下载PDF
L-fuzzy拓扑空间中的相对T_i(i=0,1,2)分离性 被引量:4
11
作者 王延军 马保国 《模糊系统与数学》 CSCD 北大核心 2009年第2期78-82,共5页
以已有文献为基础,在L-fuzzy拓扑空间中引入了L-fuzzy相对Ti(i=0,1,2)分离性公理,给出了它们的特征刻画,讨论了它们之间的关系,并研究了它们的一系列基本性质,如可遗传性、L-fuzzy同胚不变性等。
关键词 L—fuzzy拓扑空间 远域 L-fuzzy相对Ti(i=0 1 2)分离性
下载PDF
I-fuzzy拓扑的基和子基 被引量:3
12
作者 王瑞英 吉智方 《内蒙古师范大学学报(自然科学汉文版)》 CAS 2007年第2期127-129,共3页
在I-fuzzy拓扑空间中引入R-邻域系,利用R-邻域系给出基和子基的概念,研究了基和子基的充分必要条件.
关键词 连续值逻辑 模糊拓扑 I-fuzzy拓扑空间 R-邻域系 子基
下载PDF
I-fuzzy拓扑空间中的Moore-Smith收敛(英文) 被引量:3
13
作者 岳跃利 方进明 《模糊系统与数学》 CSCD 2004年第4期18-24,共7页
用方进明提出的 I-fuzzy拟重邻域系研究 I-fuzzy拓扑空间中的 Moore-Smith收敛性 ,给出它的应用 。
关键词 I-fuzzy拓扑 I-fuzzy拟重邻域系 网收敛 滤子收敛
下载PDF
Fuzzy拓扑空间中分离性的一点注记 被引量:2
14
作者 冯玉英 宣立新 《南京师大学报(自然科学版)》 CAS CSCD 2002年第3期39-43,共5页
在Fuzzy拓扑空间中引入了N-T0,N-T1分离性概念,这不仅使分明的T0,T1拓扑空间分别成为N-T0,N-T1拓扑空间的特款,而且揭示了在Fuzzy拓扑空间中的T0,T1分离性与层次分离性(T-1),N-T0,N-T1间的分解关系.文中还讨论了这两个分离性的性质.
关键词 fuzzy拓扑空间 N-T0分离性 N-T1分离性 远域 层次分离性 整体分离性 N-T0空间 N-T1空间
下载PDF
Fuzzy拓扑环 被引量:1
15
作者 郭双冰 党发宁 《四川师范大学学报(自然科学版)》 CAS CSCD 1994年第3期107-110,共4页
本文利用重域定义了Fuzzy拓扑环,并且给出了Fuzzy拓扑环的一些性质。
关键词 重域 模糊拓扑 模糊拓扑环
下载PDF
I-Fuzzy拓扑空间中的θ-连续函数 被引量:2
16
作者 韩刚 吉智方 《模糊系统与数学》 CSCD 北大核心 2007年第3期9-15,共7页
利用R-邻域系在I-fuzzy拓扑空间中定义θ-闭包、θ-内部、Rθ-邻域系和θ-连续函数,并且研究它们的一些性质。
关键词 I-fuzzy拓扑空间 R-邻域系 θ-闭包 θ-连续
下载PDF
L-Fuzzy闭包空间的紧性和分离性 被引量:10
17
作者 尤飞 《纺织高校基础科学学报》 CAS 2001年第3期217-218,229,共3页
在 LF闭包空间中 ,定义了 Ti(i =1 ,2 ,3 ,4)空间的分离性 .证明了这样定义的空间的分离性是协调的 .证明了紧 T2 空间既是 T3空间又是 T4空间 .
关键词 LF闭包空间 包域 紧集 分离性
下载PDF
L-fuzzy保序算子空间的ω-基及其性质 被引量:17
18
作者 陈水利 《江汉石油学院学报》 EI CSCD 北大核心 2003年第3期143-145,共3页
在L-fuzzy保序算子空间中引入ω^-基、ω^-子基、ω^-远域基和ω^-远域子基等概念。系统地研究了ω^-基、ω^-子基、ω^-远城基和ω^-远城子基这些概念的性质以及它们之间的关系,同时给出了这些概念在刻画序同态的ω^-连续性以及分子网... 在L-fuzzy保序算子空间中引入ω^-基、ω^-子基、ω^-远域基和ω^-远域子基等概念。系统地研究了ω^-基、ω^-子基、ω^-远城基和ω^-远城子基这些概念的性质以及它们之间的关系,同时给出了这些概念在刻画序同态的ω^-连续性以及分子网和理想的ω^-收敛性的若干应用。 展开更多
关键词 L-fuzzy保序算子空间 ω-基 ω-子基 ω-远域基 ω-远域子基 ω-开集 ω-闭集 序同态
下载PDF
L-fuzzy相对T_1与相对T_2分离性 被引量:2
19
作者 李尧龙 《江西师范大学学报(自然科学版)》 CAS 北大核心 2005年第5期420-423,共4页
定义了L-fuzzy拓扑空间中的相对T1与相对T2分离性,讨论了相对T1与相对T2分离性的一系列性质,证明了相对T1与相对T2分离性是遗传的、传递的(弱)同胚不变的,并且具有可乘性,并对相对T1与T1分离性,相对T2与T2分离性作了比较.
关键词 L-fuzzy相对T1分离性 L-fuzzy相对T2分离性 分子 远域
下载PDF
L-fuzzy拓扑空间中一种新的T_1分离性 被引量:3
20
作者 刘智斌 《陕西师大学报(自然科学版)》 CSCD 北大核心 1999年第2期17-19,共3页
研究了L-fuzzy拓扑空间的分离性问题.引入了一种新的T1分离性,给出了它的等价刻画,证明了这样的T1分离性有可乘性、L-好的推广、弱同胚不变性等性质。
关键词 LF拓扑空间 分离性 远域 强同胚 T1分离性
下载PDF
上一页 1 2 14 下一页 到第
使用帮助 返回顶部