Showing 1 - 20 results of 12,572 for search '(( algorithm 1 function ) OR ((( algorithm python function ) OR ( algorithm density function ))))*', query time: 1.37s Refine Results
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    Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

    Published 2019
    “…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”
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    Performance of the smooth-index algorithm for matrices with different densities. by Alexander Borst (32619)

    Published 2024
    “…<p><b>A</b> Example matrices for N = 50 neurons, given a density of 50% in the lower triangle<b>. B</b> Performance of the algorithm as a function of the number of neurons. …”
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    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

    Published 2025
    “…For a RDKit molecule, it provides (i) a PNG binary string with an image of the molecule with color-highlighted functional groups; (ii) a list of sets of atom indices (idx), each set corresponding to a functional group; (iii) a list of pseudo-SMILES canonicalized strings for the full functional groups; and (iv) a list of RDKit labeled mol objects, one for each full functional group. …”
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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”
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    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

    Published 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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    Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

    Published 2025
    “…Kohn–Sham density functional theory (KS-DFT) has become a cornerstone for studying the electronic structure of molecules and materials. …”
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    A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

    Published 2025
    “…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”
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    An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

    Published 2020
    “…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b><sup>0</sup> (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”
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    The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

    Published 2024
    “…Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”