PSO parameters and objective function. by André G. Coimbra (21354135)

GA parameters and objective function. by André G. Coimbra (21354135)

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

NRPStransformer, an Accurate Adenylation Domain Specificity Prediction Algorithm for Genome Mining of Nonribosomal Peptides by Zhihan Zhang (1403308)

“…The efficacy of our prediction tool was validated through targeted genome mining, which led to the discovery of novel antimicrobial peptides. …”

State Function-Based Correction: A Simple and Efficient Free-Energy Correction Algorithm for Large-Scale Relative Binding Free-Energy Calculations by Runduo Liu (10756379)

“…We present an efficient and straightforward State Function-based Correction (SFC) algorithm, which leverages the state function property of free energy without requiring cycle identification. …”

The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)

<b></b>Magnetic Kernels: A Theoretical and Algorithmic Framework for the P vs NP Problem by DURGHAM QARALLEH (21904172)

S and V shaped transfer functions. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Siou loss function calculation diagram. by Weiyu Han (3448742)

Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty by Arnaud Liehrmann (10970682)

“…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …”

The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”

Algorithm parameter settings. by Tao Dong (15551)

“…The results revealed that the improved multi-objective differential evolution algorithm in Zitzler-Deb-Thiele 1 function test had generational distance of 0.0513, inverted generational distance of 0.3265, and hyper volume metric of 0.1301. …”

Training loss function curve. by Mingtao Gao (21722035)

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…The Pareto optimal front was generated using MOCOA with the indicators of spectral kurtosis and KL divergence, by which the optimal intrinsic mode functions were obtained. …”

Flowchart of MOSRS algorithm. by Vahid Goodarzimehr (21343124)

“…The source codes of the MOSRS algorithm are publicly available at <a href="https://nimakhodadadi.com/algorithms-+-codes" target="_blank">https://nimakhodadadi.com/algorithms-+-codes</a>.…”

A Dataset of Curie and Neel Temperatures auto-generated with ChemDataExtractor and the Snowball Algorithm by Charles Kelly (21712413)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

“…The only algorithms with non-diagonal ROCs are PATH⁻ (AUC=0.696), and the three scoring functions tested with the full AutoDock framework: Vina (AUC=0.69), Smina (AUC=0.71), and Idock (AUC=0.68). …”

Fitness comparison on test function. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”