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algorithms within » algorithm within (Expand Search)
algorithm python » algorithm within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
within function » fibrin function (Expand Search), protein function (Expand Search), catenin function (Expand Search)
algorithm pca » algorithm a (Expand Search), algorithm cl (Expand Search), algorithm co (Expand Search)
pca function » gpcr function (Expand Search), a function (Expand Search), fc function (Expand Search)
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The SSIM for the different algorithms.
Published 2024“…Unlike traditional threshold functions, the improved threshold function is a continuous function that can avoid the pseudo Gibbs effect after image denoising and improve image quality. …”
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Taming Negative Ion Resonances Using Nonlocal Exchange-Correlation Functionals
Published 2024Subjects: -
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Hierarchical sparse functional principal component analysis for multistage multivariate profile data
Published 2020“…The proposed HSMFPCA employs the regression-type reformulation of the PCA and the reparameterization of the entries of eigenvectors, and enjoys an efficient optimization algorithm in high-dimensional settings. …”
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Algorithm parameter levels.
Published 2024“…Alternatively, the formulated objective functions often deviate from real-world scenarios. …”
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Parselmouth for bioacoustics: automated acoustic analysis in Python
Published 2023“…Five years ago, the Python package Parselmouth was released to provide easy and intuitive access to all functionality in the Praat software. …”
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Comparison of different algorithms.
Published 2025“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”
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Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information.
Published 2024“…Whiskers show the lowest and highest values within 1.5 × <i>IQR</i> from the first and third quartiles, respectively. …”
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Table_4_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX
Published 2022“…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …”