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

Testing function diagram of QIMPN-PCA-DC. حسب Jun Zhao (59250)

Standard benchmark functions used for the experimentation of EOSA and other similar optimization algorithms. حسب Tehnan I. A. Mohamed (16846175)

The optimization results of the objective function. حسب Shenjie Cheng (18563736)

Effect of the transmission probability function on epidemic spread. حسب Soler Gabriela Bayolo (21011810)

The loss function of network structures, LPC-DNN, LPC-PCA-DNN, LPC-LSTM, LPC-PCA-LSTM, MFCC-DNN, MFCC-PCA-DNN, MFCC-LSTM and MFCC-PCA-LSTM, as the epoch increases. حسب Cihun-Siyong Alex Gong (11874066)

Probability density functions (PDFs) of the simulated surveillance noise. حسب Sandor Beregi (22177739)

Convergent curves of EOSA and related optimization algorithms benchmark functions over 1, 50, 100, 200, 300, 400 and 500 epochs. حسب Tehnan I. A. Mohamed (16846175)

The optimal contact/quarantine rates from the family of functions (4) and (5) for Hainan and Xinjiang. حسب Mengqi He (5753525)

الموضوعات:

Reconstructing <i>sparse</i>, binary patterns using message passing algorithms and PCA. حسب Sebastian Goldt (14522594)

"…<p>We plot the mse per pattern obtained by the AMP algorithm, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e072" target="_blank">Eq (32)</a>, as a function of the effective noise Δ (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e032" target="_blank">9</a>), for random (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e044" target="_blank">15</a>) and informed (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e045" target="_blank">16</a>) initialisations. …"

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

الموضوعات:

Swarm intelligence algorithms for width and length on influence games حسب Francisco Muñoz (9455441)

"…<br><br><div>usage: Main.py [-h] [-a] [-r] [-d D] [-t T] [-i I] [-q Q] [--shape SHAPE] [--sym] [--folder FOLDER] [--seed SEED] [--sum SUM] [--mh MH] [--tagsfile TAGSFILE] [--notags] [--prune] [--excludenodes EXCLUDENODES]<br><br>Calculates the best Influence Spread set on a Weighted Symmetric Graph using PSO<br></div><div><br></div><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: threat file input contents as an Adjacency Matrix</div><div> -r: reverse order of nodes, from (a,b,w) a -> b will be b -> a</div><div> -d D: line separator to use while parsing</div><div> -t T: number of times to execute</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 calcs</div><div> --sum SUM: adds a value to all node labels</div><div> --mh MH: metaheuristic to use - list of implemented metaheuristics: {1: 'Swarm', 2: 'Swarm2', 3: 'Swarm_W', 4:</div><div> 'Swarm_L'}</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 - tags will be calculated</div><div> --prune: nodes with outdegree = 0 and indegree > 0, and with outdegree = 1 and neighbor's outdegree > 0 will be excluded</div><div> --excludenodes EXCLUDENODES: nodes to skip, comma separated</div></div>…"

PCA calculation FRHGs score. حسب Lixia Chen (614030)

الموضوعات:

Bayesian algorithm’s network type flow chart. حسب Kottakkaran Sooppy Nisar (11564911)

Infrared Spectroscopy Coupled with Machine Learning Algorithms to Investigate Vascular Dysfunction in Ovariectomy: An Animal Model Study حسب Tháfanys S. Travezani (20609398)

Principal Component Analysis (PCA) of the independent dataset from the HPC cohort. حسب Erica A. K. DePasquale (11851483)

الموضوعات:

Shows the LL component of output from the wavelet filter function for normal, benign, and malignant lung cancer samples. حسب Tehnan I. A. Mohamed (16846175)

Convergent curves of EOSA on standard benchmark functions over 1, 50, 100, 200, 300, 400 and 500 epochs. حسب Tehnan I. A. Mohamed (16846175)

Swarm intelligence algorithms for multi-objective max-min-ISP حسب Francisco Muñoz (9455441)

"…<p>Algorithms implemented on article "<strong>On the max-min influence spread problem: A multi-objective optimization approach</strong>"</p> <p><br></p> <p>usage: Main.py [-h] [-a] [-r] [-d D] [-t T] [-i I] [-q Q] [--shape SHAPE] [--sym] [--folder FOLDER] [--seed SEED] [--spread SPREAD] [--sum SUM] [--mh MH] [--tagsfile TAGSFILE] [--notags] [--prune] [--prunelowdeg] [--excludenodes EXCLUDENODES] [--includeindegzero] [--nodepthcriteria] [--memfile MEMFILE] file</p> <p><br></p> <p>Calculates the best Influence Spread set on a Weighted Graph using PSO</p> <p><br></p> <p>positional arguments:</p> <p>file</p> <p><br></p> <p>options:</p> <p>-h, --help: show this help message and exit</p> <p>-a: read file input contents as an Adjacency Matrix</p> <p>-r: reverse nodes order, reads (b,a,w) instead of (a,b,w)</p> <p>-d D: line separator to use on file parsing</p> <p>-t T: number of times to execute this solver</p> <p>-i I: number of metaheuristic iterations per execution</p> <p>-q Q: fixed quota, use 0 = floor(n/2)+1</p> <p>--shape SHAPE: shape functions for binarization - list of implemented shape functions: s2, s2_neg, v2, v4</p> <p>--sym: consider graph as symmetric instead of directed</p> <p>--folder FOLDER: output folder</p> <p>--seed SEED: use custom seeds for metaheuristic pseudo RNG</p> <p>--spread SPREAD: use specific influence spread model funcion - list of implemented models: LT, IC</p> <p>--sum SUM: adds an extra value to all edge's weight</p> <p>--mh MH: metaheuristic to use - list of implemented metaheuristics: 1 (Swarm3), 3 (Swarm3_W), 4 (Swarm3_L), 5 (Swarm4)</p> <p>--tagsfile TAGSFILE: use first row as node tags instead of using plurality criteria</p> <p>--notags: do not use first row as node tags, instead tags will be calculated</p> <p>--prune: nodes with (1) outdegree = 0 and indegree > 0, and (2) with outdegree = 1 and neighbor's outdegree > 0 will be excluded</p> <p>--prunelowdeg: nodes with low outdegree or degree will be excluded</p> <p>--excludenodes EXCLUDENODES: nodes to skip, must be comma separated</p> <p>--includeindegzero: forces to include nodes with indegree = 0 on all executions</p> <p>--nodepthcriteria: particles will not tie off with spread depth in case of having same fitness and spread</p> <p>--memfile MEMFILE: memory dump of other execution</p>…"

Swarm intelligence algorithms for multi-objective IMP: Step-by-step improvement حسب 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>…"