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

Comparison of the curves of the DCIOU loss function and the CIOU loss function. by Xunqian Xu (21261899)

Subjects:

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…”

Algorithm operation steps. by Junyan Wang (4738518)

“…To address these issues, this paper proposes an improved object detection algorithm named SCI-YOLO11, which optimizes the YOLO11 framework from three aspects: feature extraction, attention mechanism, and loss function. …”

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

Loss function curve. by Xiangqian Xu (17310895)

Subjects:

The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Convergence curve of unimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

Subjects:

Convergence curve of unimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Subjects:

Training loss function curve. by Mingtao Gao (21722035)

A hybrid algorithm based on improved threshold function and wavelet transform. by Bingbing Li (461702)

Subjects:

The SSIM for the different algorithms. by Bingbing Li (461702)

Subjects:

Loss functions between PCA-DNN model and PCA-LSTM model. by Cihun-Siyong Alex Gong (11874066)

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…In medicinal chemistry, they are the basis for analyzing ligand–biomacromolecule interactions. Ertl’s algorithm is an approach to extract functional groups in arbitrary organic molecules that does not depend on predefined libraries of functional groups. …”

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). …”

<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.…”

Performance of the three algorithms. by Juanjuan Lin (2096830)

“…<div><p>Disruptive events cause decreased functionality of transportation infrastructures and enormous financial losses. …”

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. …”