Results 61 to 70 of about 4,584 (156)

Research on Recognition Method of Driving Fatigue State Based on Sample Entropy and Kernel Principal Component Analysis

Entropy, 2018
In view of the nonlinear characteristics of electroencephalography (EEG) signals collected in the driving fatigue state recognition research and the issue that the recognition accuracy of the driving fatigue state recognition method based on EEG is still
Beige Ye, Taorong Qiu, Xiaoming Bai, Ping Liu   +3 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

Nonlinear Model for Condition Monitoring and Fault Detection Based on Nonlocal Kernel Orthogonal Preserving Embedding

Shock and Vibration, 2018
The dimension reduction methods have been proved powerful and practical to extract latent features in the signal for process monitoring. A linear dimension reduction method called nonlocal orthogonal preserving embedding (NLOPE) and its nonlinear form ...
Bo She, Fuqing Tian, Weige Liang, Gang Zhang   +3 more
doaj   +1 more source

NC Machine Tools Fault Diagnosis Based on Kernel PCA and k-Nearest Neighbor Using Vibration Signals

Shock and Vibration, 2015
This paper focuses on the fault diagnosis for NC machine tools and puts forward a fault diagnosis method based on kernel principal component analysis (KPCA) and k-nearest neighbor (kNN).
Zhou Yuqing, Sun Bingtao, Li Fengping, Song Wenlei   +3 more
doaj   +1 more source

基于特征评估与核主分量分析的齿轮故障分类方法

Jixie chuandong, 2014
For the blindness and one-sidedness of selection and fusion of mechanical fault features without priori knowledge,a novel method of gear fault feature extraction and classification based on feature evaluation and kernel principal component analysis is ...
瞿雷, 戴光昊, 王琇峰, 沈玉娣
doaj  

Signal processing methods for EEG data classification [PDF]

, 2008
Imperial Users ...
Varnavas, Andreas Soteriou, Varnavas, Andreas Soteriou   +1 more
core  

Kernel Principal Component Analysis for Allen–Cahn Equations

Mathematics
Different researchers have analyzed effective computational methods that maintain the precision of Allen–Cahn (AC) equations and their constant security.
Yusuf Çakır, Murat Uzunca
doaj   +1 more source

Fusion Maximal Information Coefficient-Based Quality-Related Kernel Component Analysis: Mathematical Formulation and an Application for Nonlinear Fault Detection

Axioms
Amid intensifying global competition, industrial product quality has become a critical determinant of competitive advantage. However, persistent quality-related faults in production environments threaten product integrity.
Jie Yuan, Hao Ma, Yan Wang
doaj   +1 more source

Rolling Bearing Reliability Assessment via Kernel Principal Component Analysis and Weibull Proportional Hazard Model

Shock and Vibration, 2017
Reliability assessment is a critical consideration in equipment engineering project. Successful reliability assessment, which is dependent on selecting features that accurately reflect performance degradation as the inputs of the assessment model, allows
Fengtao Wang, Xutao Chen, Bosen Dun, Bei Wang, Dawen Yan, Hong Zhu   +5 more
doaj   +1 more source

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