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

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

Limitation of the conventional DBT reconstruction algorithm. by Yunsu Choi (11993484)

Curve of step response signal of 6 algorithms. by Guangwei Liu (181992)

“…Secondly, the nonlinear convergence factor is constructed to replace the original random factor <i>c</i>₁ to coordinate the algorithm’s local exploitation and global exploration performance, which effectively improves the ability of the algorithm to escape extreme values and fast convergence. …”

Step by step comparison of enrichment algorithms. by Nicholas Markarian (18251668)

Network structure of perception fusion algorithm. by Weilin Wu (13736)

Subjects:

The main steps of the general algorithm. by Dror Mughaz (18017583)

Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

“…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

The real NGD values, one-step ahead training set predictions, and multi-step ahead test set predictions using the AI-AFTER algorithm for Kayseri. by Burak Alakent (463512)

Statistical results of various algorithms. by ZeSheng Lin (20501356)

Subjects:

Swarm intelligence algorithms for multi-objective IMP: Step-by-step improvement by Francisco Muñoz (9455441)

“…</div><div><br></div><div>positional arguments: </div><div> file </div><div><br></div><div>optional arguments: </div><div> -h, --help: show this help message and exit </div><div> -a: read file input contents as an Adjacency Matrix </div><div> -r: reverse nodes order, reads (b,a,w) instead of (a,b,w) </div><div> -d D: line separator to use on file parsing </div><div> -t T: number of times to execute this solver </div><div> -i I: number of metaheuristic iterations per execution </div><div> -q Q: fixed quota, use 0 = floor(n/2)+1 </div><div> --shape SHAPE: shape functions for binarization - list of implemented shape functions: s2, s2_neg, v2, v4 </div><div> --sym: consider graph as symmetric instead of directed </div><div> --folder FOLDER: output folder </div><div> --seed SEED: use custom seed for metaheuristic pseudo RNG </div><div> --spread SPREAD: use specific influence spread model funcion - list of implemented models: LT, IC </div><div> --sum SUM: adds an extra value to all edge's weight --mh MH: metaheuristic to use - list of implemented metaheuristics: 1 (Swarm3) </div><div> --tagsfile TAGSFILE: use first row as node tags instead of using plurality criteria </div><div> --notags: do not use first row as node tags, instead tags will be calculated </div><div> --prune: nodes with (1) outdegree = 0 and indegree > 0, and (2) with outdegree = 1 and neighbor's outdegree > 0 will be excluded </div><div> --prunelowdeg: nodes with low outdegree or degree will be excluded </div><div> --excludenodes EXCLUDENODES: nodes to skip, must be comma separated </div><div> --includeindegzero: forces to include nodes with indegree = 0 on all executions </div><div> --nodepthcriteria: particles will not tie off with spread depth in case of having same fitness and spread </div>…”

Comparison of step size 0.1 with the actual energy consumption step count. by Zhiqun Lin (1429501)

Subjects:

Flowchart of step() function. by Raed Alharthi (18340157)

Algorithm of the brightness scale calibration experiment. by Krzysztof Petelczyc (3954203)

“…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …”

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

Subjects:

Great machine learning performance with multiple classification algorithms. by Sydney C. Weiser (15383531)

Flowchart outlining the spectral analysis reconstruction algorithm for quantitative phase imaging using non-telecentric DHM systems. by Brian Bogue-Jimenez (16954568)

Subjects: “…developed computational algorithm…”

Node matching step 1. by Shuwen Wang (457921)

Subjects:

Algorithm of genetic workup. by Idoia Martinez de Lapiscina (16528261)