Flowchart of one iteration of the CE-Symm algorithm. by Spencer E. Bliven (6672755)

Multi-Objective Cooperative Paths Planning for Multiple Parafoils System Using a Genetic Algorithm by Chen Qi (2803873)

“…Parafoils’ paths are encoded by real matrix, and the cooperative relationship between parafoils is realized by paths fitness function. The random single point crossover and Gaussian mutation are introduced to accelerate algorithm convergence rate. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

“…We benchmark the strategy against one- and two-dimensional nearest-neighbor Heisenberg models, the one-dimensional next-nearest-neighbor Heisenberg model, and <i>selected</i> collinear ground and excited states of the nitrogenase P-cluster, employing intermediate CAS(48,40) active space ab initio Hamiltonians. …”

Benchmark functions. by Yun Qi (560401)

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from table 1 with 1000 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from table <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">1</a> with 1000 dimensions.…”

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from Table 1 with 30 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">Table 1</a> with 30 dimensions.…”

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from Table 1 with 100 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">Table 1</a> with 100 dimensions.…”

Comparative analysis of algorithms. by Xumin Zhao (18261643)

“…Notably, the LIRU algorithm registers a 5% increment in one-hop hit ratio relative to the LFU algorithm, a 66% enhancement over the LRU algorithm, and a 14% elevation in system hit ratio against the LRU algorithm. …”

Proportional survival plot of asymptotic, linear, logistic, and pseudo-gamma functional forms against growth time. by Ryu B. Lippmann (14797597)

Observed distributions of ARI ×100 from the FRECL partition after consensus clustering; against the number of runs. by Susana Conde (5495675)

Subjects:

Function testing and iterative variation diagram. by Yun Qi (560401)

Observed adjusted Rand index for one-replicate simulations (with AR(1), <i>ρ</i> = 0.5, <i>σ</i>² = 0.1) against the number of clusters <i>K</i> = 3, 6, 9, 12 (on the ho... by Susana Conde (5495675)

Subjects:

Line plots with the ARI for the simulations with one replicate against the number of clusters for FRECL and the five alternative methods for simulated data sets. by Susana Conde (5495675)

Subjects:

Line plots with the RI for the simulations with one replicate against the number of clusters for FRECL and the five alternative methods for simulated data sets. by Susana Conde (5495675)

Subjects:

Line plots with the TPR for the simulations with one replicate against the number of clusters for FRECL and the five alternative methods for simulated data sets. by Susana Conde (5495675)

Subjects:

Line plots with the TNR for the simulations with one replicate against the number of clusters for FRECL and the five alternative methods for simulated data sets. by Susana Conde (5495675)

Subjects:

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. …”

Type-1 membership function for distance. by Seung-Min Ryu (21463891)

“…<div><p>In this study, we present an algorithm to estimate the distance between a vehicle and a target object using light from headlights captured by a camera. …”

Type-1 membership function for speed. by Seung-Min Ryu (21463891)

“…<div><p>In this study, we present an algorithm to estimate the distance between a vehicle and a target object using light from headlights captured by a camera. …”