Search Results - (( simulation using pca algorithm ) OR ( java implication based algorithm ))
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1
Improved nu-support vector regression algorithm based on principal component analysis
Published 2023“…The performance of the proposed PCA-SVR algorithm is extensively assessed by two real data sets and simulation studies. …”
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Article -
2
Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…Both simulation on bivariate and multivariate cases show some promising results that the weighted PCA on LDA and the weighted PLS on LDA are better than the traditional LDA, kernel discriminant, and PCA+LDA methods. …”
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Monograph -
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Optimized clustering with modified K-means algorithm
Published 2021“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. The developed algorithms were tested on uncorrelated and correlated simulated data sets, generated under various conditions. …”
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Thesis -
5
The performance of k-means clustering method based on robust principal components
Published 2018“…To remedy this problem, we proposed to integrate robust principal component analysis (RPCA) with the k-means algorithm. Simulation study and real examples are carried out to compare the performance of the classical k-means, k-means based on PCA and k-means based on RPCA. …”
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Methods We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. …”
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7
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Therefore, in this project, Principal Component Analysis (PCA) is used to reduce the number of parameters. …”
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Final Year Project -
8
Infomax and FASTICA using principle component analysis as preprocessor for airwave removal in seabed logging
Published 2014“…Hence, the Infomax and FASTICA de-convolution algorithms are used, considering PCA as a pre-processor to filter out the airwaves which disrupt the subsurface signals within the receiver response. …”
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Conference or Workshop Item -
9
Classification for large number of variables with two imbalanced groups
Published 2020“…Both proposed algorithms outperform the conventional LDA on principal components (PCA-LDA) in classifying the minority group. …”
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Thesis -
10
Minimum regularized covariance determinant and principal component analysis-based method for the identification of high leverage points in high dimensional sparse data
Published 2022“…A simulation study and two real data sets are used to illustrate the merit of our proposed method compared to the RMD-MRCD and Robust PCA (ROBPCA) methods. …”
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11
Detection and Severity Identification of control valve stiction in industrial loops using integrated partially retrained CNN-PCA frameworks
Published 2021“…In this thesis, an integrated framework using such partially retrained convolutional neural networks in conjunction with principal component analysis (CNN-PCA) is proposed for simultaneous control valve stiction detection and automatic identification of the severity of the problem. …”
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Thesis -
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Comparing three methods of handling multicollinearity using simulation approach
Published 2006“…The analysis including all simulations and calculations were done using statistical package S-Plus 2000 software.…”
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Fault detection and diagnosis using correlation coefficients
Published 2005“…Normal Correlation (NC), Principal Component Analysis (PCA) and Partial Correlation Analysis (PCorrA) are used to develop the correlation coefficients between the selected key process variables with the quality variables of interest in the process from the NOC data. …”
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Thesis -
15
Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network
Published 2016“…The simulated Landsat TM and AVNIR-2 data were tested against in situ reflectance spectra measurements using ASD Spectroradiometer. …”
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Thesis -
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Multi-modal association learning using spike-timing dependent plasticity (STDP)
Published 2014“…Prior to a learning simulation, we extract the features of the biometrics used in the study. …”
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Thesis -
17
On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay
Published 2024“…The results obtained from the simulation studies and application to real data showed that FDGM performed better than GM when PCA and LDA were employed. …”
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Thesis -
18
Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)
Published 2006“…The developed FDD algorithm was implemented on a simulated distillation column which is a single equipment process. …”
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Monograph -
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A Comparative Study On Some Methods For Handling Multicollinearity Problems
Published 2006“…The analysis including all simulations and calculations were done using statistical package S-Plus 2000 software. …”
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A comparative study on some methods for handling multicollinearity problems
Published 2006“…The analysis including all simulations and calculations were done using statistical package S-Plus 2000 software. …”
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