Showing 101 - 120 results of 14,293 for search '(( algorithm python function ) OR ((( algorithm b function ) OR ( algorithm using function ))))', query time: 0.85s Refine Results
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    BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

    Published 2019
    “…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”
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    <b>Fig. 3 | Performance analysis of microrobot navigation in various environments using reinforcement learning algorithms.</b> by Mahmoud Medany (20766911)

    Published 2025
    “…<b>e.</b> Impact of different reward functions on the rate of target achievement. …”
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    Experiment 2D and 5D: Progressive Sample Scaling Algorithm To Solve Many-Affine BBOB Functions. by Boris Almonacid (4110337)

    Published 2024
    “…For this specific experiment<a href="https://markdownlivepreview.com/#cite_note-2" target="_blank"><sup>[2]</sup></a><a href="https://markdownlivepreview.com/#cite_note-3" target="_blank"><sup>[3]</sup></a>, the average AOCC is calculated.</p><p dir="ltr"><b>Objectives</b></p><ul><li>Solve Many-Affine BBOB Functions using a Deterministic Algorithm.…”
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    Details of S-shaped and V-shaped functions. by Yan Wei (32168)

    Published 2023
    “…Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. …”
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    Relearning under noisy feedback signal using recursive-least-squares algorithm and local learning algorithm [47]. by Barbara Feulner (10104552)

    Published 2021
    “…<p>(A-B) Relearning performance, measured as mean squared error (MSE), as a function of the amplitude of the noise in the feedback signal using recursive-least-squares (RLS) algorithm (A) and an alternative implementation with a local learning algorithm (Eprop) (B). …”