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

Subjects:

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

Graph of convergence of PSO algorithm fitness function. by Mohammed F. Elnaggar (18297954)

“…<p>Graph of convergence of PSO algorithm fitness function.</p>…”

Functional fitness test results of different algorithms. by Ling Zhao (111365)

“…<p>Functional fitness test results of different algorithms.…”

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)

Fitting results of each function. by Hui Huang (4122)

Boxplot of fitness in various algorithms. by Wei Liu (20030)

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

Fitness function parameters. by Ankita Sharma (3183054)

Values of the fitness function for different algorithms run on various companies’ datasets. by Bitanu Chatterjee (15295261)

“…<p>Values of the fitness function for different algorithms run on various companies’ datasets.…”

Fitting results of the different optimization algorithms applied. by Sonja Langthaler (6069149)

The results of 12 benchmarking functions of the maximum fitness function values. by Chuang Zhang (2199421)

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). …”

Function fitting plot. by Wang Xiang (5435141)

<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.…”

Fitness curves of the 6 test functions. by Peiwen Zhang (1863202)

(a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions). by Yu Liu (6938)

Subjects:

The results of 12 benchmarking functions of the best (minimum) fitness function values. by Chuang Zhang (2199421)

The results of 12 benchmarking functions in terms of the average fitness function values. by Chuang Zhang (2199421)

Comparison results of the compared algorithms on CEC’2013 functions with 6 × 105 fitness evaluations. by Ke Lu (124270)

“…<p>Comparison results of the compared algorithms on CEC’2013 functions with 6 × 105 fitness evaluations.…”