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.…”

System no-load torque response results under three control algorithms. by Haoran Cui (7235234)

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Schematic diagram of sliding mode variable structure control algorithm design content. by Haoran Cui (7235234)

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<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.…”

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

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

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

Towards excellent reverse learning strategy. by Peng Yao (448155)

“…Alternatively, the formulated objective functions often deviate from real-world scenarios. …”

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). …”

The top 2 ROI pairs contributing towards the classification of multi-electrode stimulation. by Anant Shinde (3954662)

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Transmission modelling functional block diagram. by Alyssa N. Sbarra (18460545)

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

Subjects: “…evolutionary genetic algorithm…”

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

Subjects: “…evolutionary genetic algorithm…”

Simulation results of sudden reduction of load torque. by Haoran Cui (7235234)

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Sensitivity analysis of parameters <i>α</i> and <i>β</i>. by Haoran Cui (7235234)

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Comparison of computational requirements for different control systems. by Haoran Cui (7235234)

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Comprehensive performance effects of three control systems under sudden load and sudden load reduction conditions. by Haoran Cui (7235234)

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Comparison results of three system related speeds. by Haoran Cui (7235234)

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Mathematical analysis process of sliding mode speed controller design based on traditional EAL. by Haoran Cui (7235234)

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