The execution times (nano seconds) per particle are measured for four different algorithms [47], (A: first algorithm, B: second algorithm, C: third algorithm: and D: fourth algorit... by Abedalmuhdi Almomany (18547669)

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …”

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

Verification of the in-line PS function. by Raul Castañeda (13932971)

Phase diagram for global archetype model as a function of temperature. by Giulio Ruffini (383994)

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Pseudo algorithm of the GA algorithm used in this study. by Tuan Anh Pham (1346049)

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Flowchart of the general algorithm for one trial. by Junying Wang (509009)

Diagram of the algorithm used during the training phase. by Ana P. Arantes (17131753)

Loss functions used in the synthetic data analysis to assess the numerical accuracy of the B-net and D-net estimates. by Jarod Smith (11999040)

Comparison results on benchmark functions with traditional algorithms. by Xiaoyi Zhang (577299)

One iteration of the NSGA-II algorithm. by Erick Axel Padilla-García (16839233)

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

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

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Comparison of benchmark function results between improved algorithms. by Xiaoyi Zhang (577299)

Convergence curves of the voltage profile improvement by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

SP results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

MS results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

(a): These systems were simulated for (0,3] and (0,3] without the prior knowledge about different phases, and the probability density function of points in feature space illustrate... by Ali Talebi (7164203)

“…(b): The dense areas are separated by removing the data less than threshold = 0.5 in the probability density function. …”

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)