Application of Fuzzy C-Means Clustering Based on Principal Component Analysis in Computer Forensics

Lecture Notes in Electrical Engineering - Future Communication, Computing, Control and Management ◽

10.1007/978-3-642-27314-8_2 ◽

2012 ◽

pp. 7-14

Author(s):

Zhi Zhong ◽

Qingdong Song ◽

Bin Ni

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Computer Forensics ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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Power Transformer Anomaly Detection Based on Adaptive Kernel Fuzzy C-Means Clustering and Kernel Principal Component Analysis

2018 Australian & New Zealand Control Conference (ANZCC) ◽

10.1109/anzcc.2018.8606615 ◽

2018 ◽

Author(s):

Kan Tang ◽

Tingzhang Liu ◽

Xiaoye Xi ◽

Yue Lin ◽

Jianfei Zhao

Keyword(s):

Principal Component Analysis ◽

Anomaly Detection ◽

Power Transformer ◽

Principal Component ◽

Component Analysis ◽

Kernel Principal Component Analysis ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering ◽

Adaptive Kernel

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Optimization of Fuzzy C-Means Clustering Algorithm with Combination of Minkowski and Chebyshev Distance Using Principal Component Analysis

International Journal of Fuzzy Systems ◽

10.1007/s40815-020-00997-5 ◽

2020 ◽

Author(s):

Sugiyarto Surono ◽

Rizki Desia Arindra Putri

Keyword(s):

Principal Component Analysis ◽

Clustering Algorithm ◽

Principal Component ◽

Component Analysis ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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Intelligent Data Pretreatment Based on Principal Component Analysis and Fuzzy C-means Clustering in Flotation Process

2007 Chinese Control Conference ◽

10.1109/chicc.2006.4347471 ◽

2006 ◽

Author(s):

Wang Jiesheng

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Flotation Process ◽

Fuzzy C Means ◽

Data Pretreatment ◽

Fuzzy C Means Clustering

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Fuzzy C-means clustering and principal component analysis of time series from near-infrared imaging of forearm ischemia

Computerized Medical Imaging and Graphics ◽

10.1016/s0895-6111(97)00018-9 ◽

1997 ◽

Vol 21 (5) ◽

pp. 299-308 ◽

Author(s):

James R. Mansfield ◽

Michael G. Sowa ◽

Gordon B. Scarth ◽

Rajmund L. Somorjai ◽

Henry H. Mantsch

Keyword(s):

Principal Component Analysis ◽

Time Series ◽

Near Infrared ◽

Infrared Imaging ◽

Principal Component ◽

Component Analysis ◽

Near Infrared Imaging ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering ◽

Analysis Of Time Series

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Using principal component analysis and fuzzy c–means clustering for the assessment of air quality monitoring

Atmospheric Pollution Research ◽

10.5094/apr.2014.075 ◽

2014 ◽

Vol 5 (4) ◽

pp. 656-663 ◽

Author(s):

Senay Cetin Dogruparmak ◽

Gulsen Aydin Keskin ◽

Selin Yaman ◽

Atakan Alkan

Keyword(s):

Principal Component Analysis ◽

Air Quality ◽

Principal Component ◽

Component Analysis ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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Application of principal component analysis and a fuzzy C-means clustering algorithm to wear debris morphology classification

Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology ◽

10.1243/13506501jet585 ◽

2009 ◽

Vol 223 (7) ◽

pp. 1059-1066 ◽

Author(s):

J P Wu ◽

X P Yan ◽

Z M Jin ◽

J L Tipper ◽

C Q Yuan ◽

...

Keyword(s):

Principal Component Analysis ◽

Wear Debris ◽

Clustering Algorithm ◽

Principal Component ◽

Component Analysis ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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Unsupervised change detection in satellite images using fuzzy c-means clustering and principal component analysis

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w2-129-2013 ◽

2013 ◽

Vol XL-7/W2 ◽

pp. 129-132 ◽

Author(s):

M. H. Kesikoğlu ◽

Ü. H. Atasever ◽

C. Özkan

Keyword(s):

Principal Component Analysis ◽

Change Detection ◽

Satellite Images ◽

Principal Component ◽

Component Analysis ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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Application of Principal Component Analysis and Fuzzy C-Means Clustering Algorithm to the Classification of UHMWPE Wear Debris from Artificial Joints

Advanced Tribology ◽

10.1007/978-3-642-03653-8_286 ◽

2009 ◽

pp. 855-856

Author(s):

J. P. Wu ◽

X. P. Yan ◽

C. Q. Yuan ◽

X. C. Zhou ◽

Z. Jin ◽

...

Keyword(s):

Principal Component Analysis ◽

Wear Debris ◽

Clustering Algorithm ◽

Principal Component ◽

Component Analysis ◽

Artificial Joints ◽

Fuzzy C Means ◽

Uhmwpe Wear ◽

Fuzzy C Means Clustering

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Robust Recommendation Algorithm Based on Kernel Principal Component Analysis and Fuzzy C-means Clustering

Wuhan University Journal of Natural Sciences ◽

10.1007/s11859-018-1301-6 ◽

2018 ◽

Vol 23 (2) ◽

pp. 111-119 ◽

Author(s):

Huawei Yi ◽

Zaiseng Niu ◽

Fuzhi Zhang ◽

Xiaohui Li ◽

Yajun Wang

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Kernel Principal Component Analysis ◽

Recommendation Algorithm ◽

Fuzzy C Means ◽

Fuzzy C Means Clustering

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A Hybrid Model Integrating Principal Component Analysis, Fuzzy C-Means, and Gaussian Process Regression for Dam Deformation Prediction

Arabian Journal for Science and Engineering ◽

10.1007/s13369-020-04923-7 ◽

2020 ◽

Author(s):

Yangtao Li ◽

Tengfei Bao ◽

Xiaosong Shu ◽

Zexun Chen ◽

Zhixin Gao ◽

...

Keyword(s):

Principal Component Analysis ◽

Gaussian Process ◽

Hybrid Model ◽

Gaussian Process Regression ◽

Principal Component ◽

Component Analysis ◽

Deformation Prediction ◽

Fuzzy C Means ◽

Dam Deformation

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