MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

MSEs for the adaptive filtering algorithms by using hyperbolic functions. by Sihai Guan (11547518)

Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

Algorithm results based on FE simulated likelihood functions. by Nicolas Herzig (9230425)

“…<p>(A) Nodule depth estimation by the algorithm with the likelihood functions obtained by FEM simulation. …”

Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”

Flowchart of proposed algorithm. by Tibebu Legesse (21030014)

“…Moreover, the proposed algorithm significantly extends network lifetime, with a <b>3.5%</b> and <b>7.5%</b> improvement over EAPS-AODV and AODV. …”

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Flowchart of DAPF-RRT algorithm. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Performance comparison of different algorithms. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Schematic diagram of the TEAPS algorithm. by Yoshiaki Kariya (13767985)

Gene function enrichment analysis: GO function enrichment analysis (A) and KEGG pathway enrichment analysis (B). by Yaling Hu (11648397)

Flowchart of the phase optimization algorithm. by Maxim Terekhov (3429614)

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

<b>The Application of the Optimized Genetic Algorithm in SerDes Circuit Design</b> by Xuan Wei (18564826)

Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. by Kevin Sawade (16726527)

“…Our ISA algorithm correlates with the much more sophisticated ROSETTA algorithm with a Pearson correlation coefficient of 0.88 (B). …”

Tunable parameters in stimuli generation module. ^<i>a</i>The fixation cross is displayed once before an experiment starts to help subjects concentrate. <sup><i>b</i></su... by Gursimran Singh (575288)

Subjects:

Proposed algorithm flowchart. by Fadhil Mukhlif (8411451)

Modeling with uniform <i>σ</i> values. by Giacomo Janson (8138517)

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

“…<p>Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.…”