Results 51 to 60 of about 7,354 (203)

Visualization of Iris Data Using Principal Component Analysis and Kernel Principal Component Analysis

Jurnal Ilmu Dasar, 2010
Principal component analysis (PCA) is a method used to reduce dimentionality of the dataset. However, the use of PCA failed to carry out the problem of non-linear and non-separable data.
Ismail Djakaria, suryo Guritno, Sri Haryatmi Kartiko   +2 more
doaj  

Enhancing Fault Detection in Stochastic Environments Using Interval-Valued KPCA: A Cement Rotary Kiln Case Study

IEEE Access
Fault detection in industrial processes is challenging due to significant data uncertainty, which complicates the accurate modeling of interval-valued data and the quantification of errors necessary for reliable detection.
Abdelhalim Louifi, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Abderazak Bensmail, Majdi Mansouri   +4 more
doaj   +1 more source

KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization

, 2014
We consider the image classification problem via kernel collaborative representation classification with locality constrained dictionary (KCRC-LCD). Specifically, we propose a kernel collaborative representation classification (KCRC) approach in which ...
Li, Hui, Liu, Weiyang, Lu, Lijia, Wen, Yandong, Yu, Zhiding, Zou, Yuexian   +5 more
core   +1 more source

One-class classifiers based on entropic spanning graphs [PDF]

, 2016
One-class classifiers offer valuable tools to assess the presence of outliers in data. In this paper, we propose a design methodology for one-class classifiers based on entropic spanning graphs.
Alippi, Cesare, Livi, Lorenzo
core   +2 more sources

A Digital Twin‐Enabled Hybrid Deep Learning Approach for Tool Wear Monitoring in CNC Milling Based on Multi‐Sensor Fusion

The Journal of Engineering, Volume 2026, Issue 1, January/December 2026.
This study proposes a digital twin‐enabled hybrid deep learning approach for tool wear monitoring in CNC milling. A four‐layer digital twin architecture is established to enable bidirectional real‐time interaction between the physical machine and its virtual model.
Shuo Wang, Zhenliang Yu, Changguo Lu, Chuanqi Li   +3 more
wiley   +1 more source

Kernel PCA feature extraction and the SVM classification algorithm for multiple-status, through-wall, human being detection

EURASIP Journal on Wireless Communications and Networking, 2017
Ultra-wideband (UWB) radar with strong anti-jamming performance and high-range resolution can be used to separate multiple human targets in a complex environment.
Wei Wang, Min Zhang, Dan Wang, Yu Jiang
doaj   +1 more source

Corrosion rate prediction model of oil-gas mixed transportation pipelines based on KPCA-IGOA-ELM

You-qi chuyun, 2023
The oil-gas mixed transportation pipeline has a high internal corrosion rate. Hence, accurately predicting the internal corrosion rate of mixed transportation pipelines is of great significance to improve the integrity management of pipelines.
LÜ Linlin, WANG Jie, QI Qingfang, GUO Ce, HE Rongrong, SUN Xiaowei   +5 more
doaj   +1 more source

Mass and Age of Red Giant Branch Stars Observed with LAMOST and \emph{Kepler}

, 2017
Obtaining accurate and precise masses and ages for large numbers of giant stars is of great importance for unraveling the assemblage history of the Galaxy. In this paper, we estimate masses and ages of 6940 red giant branch (RGB) stars with asteroseismic
Bi, Shaolan, Ge, Zhishuai, Hon, Marc, Huang, Yang, Li, Tanda, Li, Yaguang, Liu, Kang, Liu, Xiaowei, Sharma, Sanjib, Tian, Zhijia, Wu, Yaqian, Xiang, Maosheng, Yu, Jie, Zhang, Jianwei, Zhang, Jinghua, Zhang, Xianfei   +15 more
core   +1 more source

Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks

International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.
Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa, Ananda Babu Jayachandra, Swathi H. Y., Mohammed Jameel, Mohamed Abouhawwash, Francesco Longo   +5 more
wiley   +1 more source

Semi-Supervised KPCA-Based Monitoring Techniques for Detecting COVID-19 Infection through Blood Tests

Diagnostics, 2023
This study introduces a new method for identifying COVID-19 infections using blood test data as part of an anomaly detection problem by combining the kernel principal component analysis (KPCA) and one-class support vector machine (OCSVM).
Fouzi Harrou, Abdelkader Dairi, Abdelhakim Dorbane, Farid Kadri, Ying Sun   +4 more
doaj   +1 more source