Comparison of different algorithms. حسب Dawei Wang (471687)

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Multi-algorithm comparison figure. حسب Dawei Wang (471687)

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Feature selection algorithm. حسب Mahmoud Zeydabadinezhad (12289570)

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Environmental setup. حسب Parthiban Aravamudhan (15338781)

"…To create a structured valid dataset, a stacked model is made by implementing the two most popular dimensionality reduction techniques Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) algorithms. …"

Reconstructing <i>sparse</i>, binary patterns using message passing algorithms and PCA. حسب Sebastian Goldt (14522594)

"…<p>We plot the mse per pattern obtained by the AMP algorithm, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e072" target="_blank">Eq (32)</a>, as a function of the effective noise Δ (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e032" target="_blank">9</a>), for random (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e044" target="_blank">15</a>) and informed (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e045" target="_blank">16</a>) initialisations. …"

Overall process planning. حسب Dawei Wang (471687)

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Model intrinsic parameter flow. حسب Dawei Wang (471687)

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A comparison of whether to add a penalty. حسب Dawei Wang (471687)

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The interleaved processes. حسب Dawei Wang (471687)

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Final optimization results. حسب Dawei Wang (471687)

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Vehicle-related parameters. حسب Dawei Wang (471687)

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The comparison in gantt result. حسب Dawei Wang (471687)

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Pseudocode of IHWGWO. حسب Dawei Wang (471687)

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Optimize process data and final results حسب Dawei Wang (471687)

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Vehicle-related parameters. حسب Dawei Wang (471687)

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Device parameter list. حسب Dawei Wang (471687)

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The process of IHWGWO. حسب Dawei Wang (471687)

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The computational results of the case. حسب Dawei Wang (471687)

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Working time of different processes (<i>h</i>). حسب Dawei Wang (471687)

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Functional PCA With Covariate-Dependent Mean and Covariance Structure حسب Fei Ding (134577)

"…<p>Incorporating covariates into functional principal component analysis (PCA) can substantially improve the representation efficiency of the principal components and predictive performance. …"