Description of unimodal benchmark functions. by Yi-Qiang Xia (20161326)

“…In essence, it prevents algorithms from settling for suboptimal solutions too soon, encouraging exploration of a broader solution space before converging, by incorporating cauchy variation and a perturbation term, MWOA achieve optimization over a wide search space. …”

Description of multimodal benchmark functions. by Yi-Qiang Xia (20161326)

“…In essence, it prevents algorithms from settling for suboptimal solutions too soon, encouraging exploration of a broader solution space before converging, by incorporating cauchy variation and a perturbation term, MWOA achieve optimization over a wide search space. …”

Braking performance and lateral stability on low-adhesion road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle s... by Honglei Pang (22693724)

Subjects:

Braking performance and lateral stability on split-μ road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sidesl... by Honglei Pang (22693724)

Subjects:

The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou. by Mengqi He (5753525)

“…<p>(a, d, g) Root mean square error(), corresponding to fitting the time-dependent contact rate learned by TDINN algorithm using <i>c</i>₁(<i>t</i>), <i>c</i>₂(<i>t</i>) and <i>c</i>₃(<i>t</i>) in Xi’an, Guangzhou and Yangzhou. …”

Images of partial benchmark functions. by ZeSheng Lin (20501356)

“…EAWOA demonstrates superior optimization accuracy compared to WOA across 21 test functions, with a notable edge on certain functions. …”

Sensitivity analysis of the TV-BayesOpt algorithm performance at tracking a periodic temporal drift when the period of the drift is offset from the covariance function period anticipated by the TV-BayesOpt algorithm. by John E. Fleming (8533956)

“…<p>The performance of a scheduler (green line), the TV-BayesOpt with a periodic temporal covariance function (purple line) and the TV-BayesOpt with a periodic and smooth forgetting covariance algorithm were estimated by calculating the AUC value for the associated cumulative regret plot for each implementation at different offset in the true temporal period.…”

Membership function. by Tuan Anh Nguyen (121944)

A comparative workflow of all six functional software tools producing GO term lists from the same dataset. by Ray Sajulga (5721518)

Improved A* algorithm flowchart. by Peiying Li (797714)

“…The study conducted algorithm validation on the TurtleBot3 mobile robot, with data sourced from experimental data from a certain college. …”

The instance of MaxCasesAverted and MaxPeaksReduced is a graph <i>G</i> constructed from the given instance of Max k-SI. by Jeffrey Keithley (14626551)

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

“…<p>(a) Radar chart of these algorithms (23 Benchmark functions), (b) The sorting diagram of these algorithms (23 Benchmark functions).…”

High-dimensional 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. …”

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. by María Victoria Waks-Serra (21578611)

An Adapted Loss Function for Censored Quantile Regression by Mickaël De Backer (5166839)

“…For practical minimization of the studied loss function, we also provide a simple algorithmic procedure shown to yield satisfactory results for the proposed estimator with respect to the existing literature in an extensive simulation study. …”

Details of S-shaped and V-shaped functions. by Yan Wei (32168)

“…Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. …”

Standard benchmark functions [42]. by Junhao Wei (6816803)

“…The performance of the canonical WOA is improved through innovative strategies: first, an initialization process using Good Nodes Set is introduced to ensure that the search starts from a higher-quality baseline; second, a distance-based guided search strategy is employed to adjust the search direction and intensity by calculating the distance to the optimal solution, which enhances the algorithm’s ability to escape local optima; and lastly, LSWOA introduces an enhanced spiral updating strategy, while the enhanced spiral-enveloping prey strategy effectively balances exploration and exploitation by dynamically adjusting the spiral shape parameters to adapt to different stages of the search, thereby more accurately updating the positions of individuals and improving convergence speed. …”

Test functions. by Kejia Liu (5699651)

“…The study employed traditional benchmark functions and conducted evaluations versus baselines Standard GEP, NMO-SARA, and MS-GEP-A to assess fitness outcomes, R² values, population diversification, and the avoidance of local optima. …”

Loss Function Comparison. by Hongwei Yue (574068)

Loss Function Comparison. by Hongwei Yue (574068)