Test function results. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

Benchmark test functions. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

Algorithm parameters. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

CEC2017 basic functions. by Tengfei Ma (597633)

“…<div><p>To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”

DMTD algorithm. by Yunhu Huang (21402795)

“…On the basis of EITO_E, we propose EITO_P algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”

Training algorithm flow. by Xing Chen (140292)

“…However, these statistical methods require collecting data from the entire research area, which consumes a significant amount of manpower and material resources. …”

Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Imperialist competition algorithm with quasi-opposition-based learning for function optimization and engineering design problems by Dongge Lei (6836915)

“…The effectiveness of the proposed QOBL-ICA is verified by testing on 20 benchmark functions and 3 engineering design problems. Experimental results show that the performance of QOBL-ICA is superior to most state-of-the-art meta-heuristic algorithms in terms of global optimum reached and convergence speed.…”

Control parameters of the SOMA algorithm. by Quoc Bao Diep (18452207)

“…To optimize this cost function, we employ the self-organizing migrating algorithm, a swarm intelligence algorithm inspired by the cooperative and competitive behaviors observed in natural organisms. …”

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

AUC scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…This strategy is integrated into a random forest algorithm by replacing the conventional voting method. …”

Recall scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…This strategy is integrated into a random forest algorithm by replacing the conventional voting method. …”

Benchmark test function results. by Ruyi Dong (9038174)

“…Finally, the Cauchy-Gaussian mutation strategy is utilized to prevent the algorithm from falling into local traps. These three steps enable LLSKSO to achieve a dynamic balance between local and global search. …”

Illustration of the unrestricted model and its training algorithm. by Yuru Song (21300760)

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Flowchart of improved FOX optimization algorithm. by Mahmood A. Jumaah (22272371)

“…Additionally, it achieved 880 wins, 228 ties, and 348 losses against 16 optimization algorithms across all involved functions and problems. …”

Run times of two algorithms. by Gourab Saha (8987405)

“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”

Flowchart for the Tabu Search Algorithm [43]. by Ferhat Yuna (21519851)

“…The mathematical model was transformed into a fitness function and a solution was provided with the Tabu Search Algorithm and Simulated Annealing. …”