The <i>ℓ</i>₂-norm of the image difference between the reconstructed image and the ground truth for a certain scale of atelectasis. حسب Rongqing Chen (249906)

الموضوعات:

Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art CEA-ES algorithms using CEC2014 functions. حسب Yang Cao (53545)

"…<p>Wilcoxon’s test results for EBJADE algorithms and other state-of-the-art CEA-ES algorithms using CEC2014 functions.…"

Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100. حسب Yang Cao (53545)

"…<p>Wilcoxon’s test results for EBJADE algorithms and other algorithms using CEC2014 functions for D = 30, 50 and 100.…"

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

Benchmark functions T-test for the proposed and compared algorithms. حسب El-Sayed M. El-kenawy (14581088)

Proposed algorithm convergence curves versus other competing algorithms for the seven benchmark functions. حسب El-Sayed M. El-kenawy (14581088)

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses حسب Dominykas Lukauskis (14143149)

"…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …"

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses حسب Dominykas Lukauskis (14143149)

"…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …"

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses حسب Dominykas Lukauskis (14143149)

"…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …"

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. حسب Olga Valba (10531121)

Flowchart of the specific incarnation of the BO algorithm used in the experiments. حسب 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. …"

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>…"

Frequency response analysis of the commonly used indicator GCaMP6s, <i>k</i>_<i>f</i> = 0.0514, <i>k</i>_<i>r</i> = 7.6, <i>L</i> = 30. حسب Nicholas A. Rondoni (21573261)

الموضوعات:

Results of the PSO-Kmeans-ANMS algorithm for the Rastrigin function. حسب Rutinaldo Aguiar Nascimento (14259594)

الموضوعات:

Results of the PSO-Kmeans-ANMS algorithm for the Rosenbrock function. حسب Rutinaldo Aguiar Nascimento (14259594)

الموضوعات:

Graphs of the regularization terms. حسب Tomokaze Shiratori (9635271)

الموضوعات:

Inverted AR and MA polynomial roots to the fitted AR(1) and ARMA(2, 1) models to the Lake Michigan-Huron data using a single parameter initialization. حسب Jesse Wheeler (18462457)

الموضوعات: "…routinely applicable algorithm…"

The results of ICA performed using PyNoetic. حسب Gursimran Singh (575288)

الموضوعات:

Table_4_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"