Test performance metrics for the final model. by Ramona Leenings (11167294)

Comparison with SOTA model in number of iterations and final cost. by Zixi Wang (459102)

Matlab code of a version using numerical optimization for Q. by Hiroko Kato Solvang (5718250)

R code for a version using numerical optimization for Q. by Hiroko Kato Solvang (5718250)

Overall rankings of optimization algorithms. by Máté Mohácsi (20469514)

HGSAA model’s partial calculation code. by Ruoqi Wang (14958062)

Node coding process. by Jun Zhao (59250)

Codes and related data. by Bo Ni (1298154)

Overall rankings of single-objective optimization algorithms. by Máté Mohácsi (20469514)

Parallel plot showing hyperparameter exploration. by Ramona Leenings (11167294)

IKM Pseudo – code. by Yingbo Mao (22522192)

S1 Code - by Gaosha Li (20570760)

Code and raw data used in this study. by Zhuolin Yang (14658411)

I-NSGA-II-RF algorithm. by Xiaohua Zeng (793632)

“…The integrated information initialization population of two filtered feature selection methods is used to optimize the I-NSGA-II algorithm, using multiple chromosome hybrid coding to synchronously select features and optimize model parameters. …”

The pareto front obtained by each algorithm. by Xiaohua Zeng (793632)

“…The integrated information initialization population of two filtered feature selection methods is used to optimize the I-NSGA-II algorithm, using multiple chromosome hybrid coding to synchronously select features and optimize model parameters. …”

Pseudo-code of MACOA. by Xingtao Wu (22139242)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

Pseudo-code for the study design model. by Jianpeng Zhang (528185)

The speciation of ANEAT model evolution. by Wenbing Shi (5806160)

“…In the experiment, we verify the effectiveness of ANEAT from multiple aspects such as data augmentation effectiveness analysis, deep learning model comparison, swarm intelligence optimization algorithm comparison, and other method comparisons. …”

The fitness of ANEAT model evolution. by Wenbing Shi (5806160)

“…In the experiment, we verify the effectiveness of ANEAT from multiple aspects such as data augmentation effectiveness analysis, deep learning model comparison, swarm intelligence optimization algorithm comparison, and other method comparisons. …”