Information of nodes and pipes of HN. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

Convergence curve of each DSM algorithms. حسب Manoj Kumar V. (18196645)

الموضوعات:

Image of the ReLU function. حسب Mengqi Yuan (4852555)

The iterative process of genetic algorithm in the upper-level model. حسب Zhipeng Huang (1759759)

الموضوعات:

Reward function related parameters. حسب Honglei Pang (22693724)

الموضوعات:

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

Algorithm parameter settings. حسب Tao Dong (15551)

"…The improved multi-objective differential evolution algorithm optimized the fuel cost as low as $2300590 and the pollution emission as low as 200285 kg. …"

Auto-tuning algorithm of the weight factors in the cost function. حسب Syed Umaid Ali (14486372)

"…<p>Auto-tuning algorithm of the weight factors in the cost function.…"

CEC2022 and CEC2017 benchmark functions. حسب Chengcheng Ding (9013862)

Code snippets to add user-specific custom functionality in PyNoetic. حسب Gursimran Singh (575288)

الموضوعات:

Modular architecture design of PyNoetic showing all its constituent functions. حسب Gursimran Singh (575288)

الموضوعات:

The probability density function for cost function g(X). حسب Matheus Sant’Ana Lima (9937809)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. حسب Gursimran Singh (575288)

الموضوعات:

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

The obtained cost function values with respect to each run of different algorithms. حسب Davut Izci (15927452)

الموضوعات:

Flowchart of proposed fitness function algorithm. حسب Ferhat Yuna (21519851)

الموضوعات:

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. حسب Gursimran Singh (575288)

الموضوعات:

Performance comparison of recent and effective algorithms for minimizing error-based cost functions. حسب Davut Izci (15927452)

الموضوعات:

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب 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). …"

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب 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.…"