Among the many accepted clustering techniques, the fuzzy clustering approach has enjoyed a growing popularity over the last decade. Contrary to 'hard' clustering methods, wherein each object is assigned to a single cluster, fuzzy clustering is capable of describing ambiguity in the data, such as ...
A robust fuzzy clustering approach is proposed to simplify the task of principal component analysis (PCA) by reducing the data complexity of an image. This approach performs well on function curves and character images that not only have loops, shazp corners and intersections but also include ...
关键词: fabrics fuzzy systems image recognition image texture principal component analysis automatic fabric analysis automatic woven fabric structure identification digital image analysis fuzzy clustering image processing 会议名称: Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE ...
The new method is based on a simultaneous approach to principal component analysis and fuzzy clustering with an incomplete data set including missing values. In the simultaneous approach, we extract local principal components by using lower rank approximation of the data matrix. The missing values ...
Considering this problem, we present a robust recommendation algorithm based on kernel principal component analysis and fuzzy c-means clustering. Firstly, we use kernel principal component analysis method to reduce the dimensionality of the original rating matrix, which can extract the effective features...
14.Evaluation on the Core Competitiveness of Real Estate Enterprises Based on Principal Component Analysis基于主成份分析的房地产企业核心竞争力评价 15.Pests Forecasting Using Fuzzy Clustering Based on Principal Component Analysis基于主成份分析的模糊聚类虫害预测模型研究 16.To Evaluate on the Quality of Life...
Kernel Principal Component AnalysisFuzzy c-Means ClusteringIn order to guarantee the normal operation of marine, an effective fault diagnosis model need to be established to determine the reason causing the fault of marine diesel engine. According to the problem of fault diagnosis of marine diesel ...
Exploratory data-driven methods such as Fuzzy clustering analysis (FCA) and Principal component analysis (PCA) may be considered as hypothesis-generating p... R Baumgartner,L Ryner,W Richter,... - 《Magnetic Resonance Imaging》 被引量: 426发表: 2000年 Size and shape variation in the painted ...
Principal Component Analysis (PCA) is a well-known tool often used for the exploratory analysis of a numerical data set. Here an extension of classical PCA is proposed, which deals with fuzzy data (in short PCAF), where the elementary datum cannot be recognized exactly by a specific number ...
Gender classification based on fuzzy clustering and principal component analysis Gender classification is one of the most challenging problems in computer vision. Facial gender detection of neonates and children is also known as a highl... H Hassanpour,A Zehtabian,A Nazari,... - 《Iet Computer...