Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100. حسب Yang Cao (53545)

"…<p>Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100.…"

Details of the 30 benchmark functions for IEEE CEC2017. حسب Yan Wei (32168)

Box plots of different algorithms on CEC2017 functions (dim = 30,100) and CEC2022 functions (dim = 20). حسب Qingwen Meng (156386)

الموضوعات:

Plots of convergence curves on 30-D benchmark functions. حسب Salisu Mohammed (772274)

Results of test functions (F1-F11) with 30 dimensions. حسب Dingming Yang (8505990)

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). …"

Convergence graph of CRLPO and eight other algorithms on six representative benchmark functions with 30 dimensions. حسب Aijun Zhu (822068)

"…<p>Convergence graph of CRLPO and eight other algorithms on six representative benchmark functions with 30 dimensions.…"

<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.…"

Convergence curve for all algorithms from F20–F30. حسب Adel Saad Assiri (9962517)

Mean and STD obtained by eight enhanced DEs and DEGH on benchmark functions at 30D. حسب Xuxu Zhong (10099054)

The results of Friedman test with 30 variables over 30 independent runs. حسب Xuxu Zhong (10099054)

CEC2017 benchmark function experiment results(dim = 30). حسب Qingwen Meng (156386)

الموضوعات:

Results obtained by different algorithms on 23 benchmark functions. حسب Yuqi Xiong (12343771)

الموضوعات:

The results of Wilcoxon’s rank-sum test compared with ten algorithms over independent 30 runs. حسب Xuxu Zhong (10099054)

S1 File - حسب Yuh-Chin T. Huang (17867207)

الموضوعات:

S1 Dataset - حسب Yuh-Chin T. Huang (17867207)

الموضوعات:

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

الموضوعات: "…evolutionary genetic algorithm…"

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

الموضوعات: "…evolutionary genetic algorithm…"

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data حسب Anthony S. Barente (14035175)

الموضوعات:

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