بدائل البحث:
algorithm python » algorithm both (توسيع البحث)
within function » fibrin function (توسيع البحث), python function (توسيع البحث), protein function (توسيع البحث)
algorithm python » algorithm both (توسيع البحث)
within function » fibrin function (توسيع البحث), python function (توسيع البحث), protein function (توسيع البحث)
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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
منشور في 2025"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"
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Distribution of cross correlations in functional connectivity in ABIDE sample.
منشور في 2024الموضوعات: -
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Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value.
منشور في 2024الموضوعات: -
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ANOVA was performed to test the differences between the algorithms for each indicator.
منشور في 2024الموضوعات: -
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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.
منشور في 2024"…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …"
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Comparison of different algorithms.
منشور في 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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