<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</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.…”

Results of searching performance of different algorithm models on the Sphere function and Griewank function. by Rui Zhang (13940)

“…<p>Results of searching performance of different algorithm models on the Sphere function and Griewank function.…”

Results of searching performance of the improved NAG algorithm on Sphere function and Griewank function. by Rui Zhang (13940)

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Reward function related parameters. by Honglei Pang (22693724)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…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). …”

Fig 7 is completed by the representation of a diffusive random walk under the approximation of a <i>δ</i>-sphere random walk. by Jean Marc Tregan (15195173)

Performance validation of different algorithms in two benchmark functions. by Wenjing Wang (181404)

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The ALO algorithm optimization flowchart. by Wenjing Wang (181404)

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The IALO algorithm solution flowchart. by Wenjing Wang (181404)

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Comparison of convergence curves of different algorithms. by Wenjing Wang (181404)

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Comparison of algorithms in two cases. by Yi Tao (178829)

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Flow of the NSGA-II algorithm. by Yi Tao (178829)

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An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by Pascal Wang (10130612)

“…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …”

Comparison of results obtained by different algorithms for solving EELD. by Wenjing Wang (181404)

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Results comparison of different optimization algorithms for dealing with ELD. by Wenjing Wang (181404)

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EELD problem solving process based on IALO algorithm. by Wenjing Wang (181404)

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Comparison of results obtained by different algorithms for solving EELD. by Wenjing Wang (181404)

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