Two-Phase Incremental Kernel PCA for Learning Massive or Online Datasets [PDF]
Complexity, 2019 As a powerful nonlinear feature extractor, kernel principal component analysis (KPCA) has been widely adopted in many machine learning applications. However, KPCA is usually performed in a batch mode, leading to some potential problems when handling ...
Feng Zhao +5 more
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Kernel Principal Component Analysis (Kpca) For The De-Noising Of Communication Signals [PDF]
, 2002 Publication in the conference proceedings of EUSIPCO, Toulouse, France ...
Koutsogiannis, G., Soraghan, J.J.
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Integrated Metabolomics-KPCA-Machine Learning framework: a solution for geographical traceability of Chinese Jujube [PDF]
Food Chemistry: XDue to widespread product adulteration, Chinese jujube (CJ), a crop of global economic importance with nutritional and medicinal properties, struggles with geographical traceability. The study introduced a Metabolomics-Kernel Principal Component Analysis
Xiaoli Wang +8 more
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Network Anomaly Detection Model Based on GSA and DE Optimizing Hybrid Kernel ELM [PDF]
Jisuanji gongcheng, 2022 To enhance the accuracy and generalization of the network intrusion detection model, this study proposes a network intrusion detection model based on the Gravitational Search Algorithm(GSA) and Differential Evolution(DE) algorithm to optimize the hybrid ...
SHENG Long, YUAN Lina, WU Nannan, JI Shaopei
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Adaptive Process Monitoring of Online Reduced Kernel Principal Component Analysis
Shanghai Jiaotong Daxue xuebao, 2022 In the case of dynamic systems, the traditional kernel principal component analysis (KPCA) method does not perform well. The moving window kernel principal component analysis method can adapt to the normal parameter drift of dynamic systems, but it needs
GUO Jinyu, LI Wentao, LI Yuan
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Applied Sciences, 2022 Fault monitoring is often employed for the secure functioning of industrial systems. To assess performance and enhance product quality, statistical process control (SPC) charts such as Shewhart, CUSUM, and EWMA statistics have historically been utilized.
Faisal Shahzad +2 more
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Wavelet and kernel dimensional reduction on arrhythmia classification of ECG signals [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2020 Electrocardiogram (ECG) monitoring is continuously required to detect cardiac ailments. At times it is challenging tointerpret the differences in the P- QRS-T curve.
Ritu Singh, Navin Rajpal, Rajesh Mehta
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Research on the Prediction of Green Plum Acidity Based on Improved XGBoost
Sensors, 2021 The acidity of green plum has an important influence on the fruit’s deep processing. Traditional physical and chemical analysis methods for green plum acidity detection are destructive, time-consuming, and unable to achieve online detection. In response,
Yang Liu +6 more
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Research on Rolling Bearing Fault Diagnosis Based on Volterra Kernel Identification and KPCA
Shock and Vibration, 2023 A rolling bearing fault diagnosis method based on the Volterra series and kernel principal component analysis (KPCA) is proposed. In the proposed method, first, the improved genetic algorithm (IGA) is used to identify the Volterra series model of the ...
Yahui Wang +3 more
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Related and independent variable fault detection method based on KPCA-SVM
Shenzhen Daxue xuebao. Ligong ban, 2023 In the real industrial process, some process variables are independent of other variables, a fault detection method of related and independent variable based on kernel principal component analysis and support vector machine (KPCA-SVM) is proposed to ...
GUO Jinyu, YU Huan, LI Yuan
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