Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. by Raul Castañeda (13932971)

Benchmark functions used and their details. by Wei Liu (20030)

Comparison of results of different algorithms. by Zhongzhong Guo (12133402)

Subjects:

Final assignment algorithm. by Negin Alisoltani (11949357)

Comparison of PSOLFWM with PSO families algorithms using t-Test. by Yong Gao (29929)

Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Convergence curve of real power transmission line loss minimization by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

“…This paper presents an effective technique to minimize the SLL and thus improve the radiation pattern of the linear antenna array (LAA) using the chaotic inertia-weighted Wild Horse optimization (IERWHO) algorithm. …”

The convergence curve of each optimization algorithm under the test function. by Hao Yang (328526)

Algorithm testing. by Ziad M. Ali (12516532)

Subjects:

Box plots of different algorithms on CEC2017 test function. by Tengfei Ma (597633)

Subjects:

Algorithm pseudocode. by Cheng-jie Chen (22272090)

Subjects:

Comparison of benchmark function results between traditional algorithms with 60 dimensions. by Xiaoyi Zhang (577299)

LF and SP optimum values using the PSOGSAHO algorithm. by Nada Ahmed Ezz-Eldien (17396553)

Data_Sheet_1_Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.PDF by Minhua Guo (18392646)

The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)