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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm blood » algorithm based (Expand Search), algorithm flow (Expand Search), algorithm both (Expand Search)
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Optimization outcome for the Rosenbrock function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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Optimization outcome for the Rastrigin function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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2D Rastrigin function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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2D Levy function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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2D Rosenbrock function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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Optimization outcome for the Levy function.
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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Details of the metaheuristic algorithms.
Published 2025“…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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Parameter settings for algorithms.
Published 2025“…<div><p>Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. …”
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Exponentially attenuated sinusoidal function.
Published 2025“…The Pareto optimal front was generated using MOCOA with the indicators of spectral kurtosis and KL divergence, by which the optimal intrinsic mode functions were obtained. A deep VMD-attention network based on MOCOA was developed for ECG signal classification. …”
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LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery
Published 2025“…To address batch effects introduced during the merging process, the Empirical Bayes algorithm from the sva package (via the ComBat function) was applied. …”
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PATH has state-of-the-art performance versus previous binding affinity prediction algorithms.
Published 2025“…<p><sup><b>a</b></sup>PATH<sup>+</sup> shows comparable or better performance with less overfitting, as evidenced by a smaller slope, with much less increase in RMSEs beyond the training dataset, compared to established binding affinity prediction algorithms spanning a variety of methods. The benchmarked algorithms include physics-based and deep learning algorithms from the famous AutoDock framework (scoring function of AutoDock4 implemented in the AutoDockFR package [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref068" target="_blank">68</a>,<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref077" target="_blank">77</a>], Vinardo [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref069" target="_blank">69</a>], GNINA [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref070" target="_blank">70</a>]), empirical (AA-Score [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref071" target="_blank">71</a>]), knowledge-based (SMoG2016 [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref072" target="_blank">72</a>]), and deep learning-based scoring functions (OnionNet [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref073" target="_blank">73</a>], PLANET [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013216#pcbi.1013216.ref074" target="_blank">74</a>]). …”
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Fitness comparison on test function.
Published 2025“…Its restrictions block GEP from successfully handling high-dimensional along with complex optimization problems. …”
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Hash function construct used in SKINNY-tk3-hash.
Published 2024“…These devices gather information from their environment and send it across a network. …”
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ClaritySpectra: Raman spectra analysis tool
Published 2025“…</li></ul><h3>PEAK FITTING </h3><ul><li>Automated background subtraction using asymmetric least squares fitting</li><li>A new suggested background feature that lets you preview the background that you like best</li><li>Interactive background fitting lets you further tune the background to perfection</li><li>Four choice of peaks: Gaussian, Lorentzian, Pseudo-Voigt, and the new Asymmetric Voigt functions</li><li>Overlapping view of how well the peaks fit with quality metrics</li><li>No need to define regions, the algorithm is smart enough to what a peak looks like.…”
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Image 4_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regre...
Published 2025“…Objective<p>Investigate the correlation between right ventricular function ultrasound indicators and the Venous Excess Ultrasound (VExUS) grading system in patients undergoing invasive mechanical ventilation (IMV), and develop a right ventricular function assessment model using VExUS grading and the Classification and Regression Tree (CART) algorithm.…”