Results 91 to 100 of about 3,257 (211)

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

Feature Extraction of Chest X-ray Images and Analysis using PCA and kPCA [PDF]

, 2018
Tuberculosis (TB) is an infectious disease caused by mycobacterium which can be diagnosed by its various symptoms like fever, cough, etc. Tuberculosis can also be analyzed by understanding the chest x-ray of the patient which is revealed by an expert ...
T, Asha, Roopa H., Asha T., H, Roopa
core   +1 more source

A Hybrid Process Monitoring and Fault Diagnosis Approach for Chemical Plants

International Journal of Chemical Engineering, 2015
Given their potentially enormous risk, process monitoring and fault diagnosis for chemical plants have recently been the focus of many studies. Based on hazard and operability (HAZOP) analysis, kernel principal component analysis (KPCA), wavelet neural ...
Lijie Guo, Jianxin Kang
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Photovoltaic Short-Term Output Power Forecast Model Based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise–Kernel Principal Component Analysis–Long Short-Term Memory

Energies
To solve the problem of photovoltaic power prediction in areas with large climate changes, this article proposes a hybrid Long Short-Term Memory method to improve the prediction accuracy and noise resistance.
Lan Cao, Haoyu Yang, Chenggong Zhou, Shaochi Wang, Yingang Shen, Binxia Yuan   +5 more
doaj   +1 more source

Predicting the trend of dissolved oxygen based on the kPCA-RNN model

, 2020
Water quality forecasting is increasingly significant for agricultural management and environmental protection. Enormous amounts of water quality data are collected by advanced sensors, which leads to an interest in using data-driven models for ...
Zhang, Yi-Fan, Peter Fitch, Thorburn, Peter J., Yi-Fan Zhang, Fitch, Peter, Peter J. Thorburn   +5 more
core   +1 more source

Lithium-ion battery fault diagnosis method based on KPCA-MTCN [PDF]

The paper proposes a method based on kernel principal component analysis (KPCA) and multi-scale temporal convolution network (MTCN) for identifying faults in lithium-ion batteries, which is crucial for ensuring the safe and stable operation of energy ...
Qipeng TAN, Yongqi LI, Peng PENG, Man CHEN, Lingxian ZHANG, Minhui WAN   +5 more
core   +1 more source

Clasificación de cáncer de mama con técnicas de análisis de la componente principal-Kernel PCA, algoritmos de máquina de vectores de soporte y regresión logística

Medisur, 2022
Fundamento: existen muchas herramientas computacionales para administrar imágenes y conjuntos de datos; reducir la dimensión de estos favorece el manejo de la información.Objetivo: reducir la dimensión de un conjunto de datos para un mejor manejo de la ...
Rosana Pirchio
doaj  

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval

IEEE Access
Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA).
Mohammed Tahar Habib Kaib, Abdelmalek Kouadri, Mohamed-Faouzi Harkat, Abderazak Bensmail, Majdi Mansouri   +4 more
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Predicting the External Corrosion Rate of Buried Pipelines Using a Novel Soft Modeling Technique

Applied Sciences
External corrosion poses a significant threat to the integrity and lifespan of buried pipelines. Accurate prediction of corrosion rates is important for the safe and efficient transportation of oil and natural gas.
Zebei Ren, Kun Chen, Dongdong Yang, Zhixing Wang, Wei Qin   +4 more
doaj   +1 more source

A data-driven study of cultural radiation and transformation in fashion design through artificial intelligence

Journal of Radiation Research and Applied Sciences
Two different datasets, a radiation data set and a translation data set, are analyzed in this paper. Machine learning (ML) models forecast both data sets.
Shuyan Sun, Rohana Binti Zur, Deyin Su, Qiumei Li, Haiqiong Yang   +4 more
doaj   +1 more source