Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

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Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

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Flowchart of proposed fitness function algorithm. by Ferhat Yuna (21519851)

“…The mathematical model was transformed into a fitness function and a solution was provided with the Tabu Search Algorithm and Simulated Annealing. …”

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)

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HIV exposure risk algorithm. HIV exposure risk algorithm based on available data from the Tonse Padmozi trial. by Anna M. Leone (22486372)

Imperialist competition algorithm with quasi-opposition-based learning for function optimization and engineering design problems by Dongge Lei (6836915)

Subjects: “…Imperialist competition algorithm…”

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

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3D visualization of the Rastrigin function from the CEC 2019 benchmark test functions. by Mahmood A. Jumaah (22272371)

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IEEE CEC 2017 benchmark function specifications. by Kankan Tang (21474968)

IEEE CEC 2022 benchmark function specifications. by Kankan Tang (21474968)

CEC2017 basic functions. by Tengfei Ma (597633)

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Selected optimal solutions from the QLNSGA-II algorithm. by Zhongfeng Li (3965060)

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If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

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DMTD algorithm. by Yunhu Huang (21402795)

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The data for Example 5 are sampled from the peaks function. by Yushi Liu (173457)

CEC2017 test function test results. by Tengfei Ma (597633)

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Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm by Gelio Alves (51850)

“…A major challenge in mass-spectrometry-based metaproteomics is accurately identifying and quantifying biological functions across the full taxonomic lineage of microorganisms. …”

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

“…</p><p dir="ltr">The package includes:</p><ul><li>Scripts for first-order analysis, third-order modeling, optimization using a Physically Grounded Merit Function (PGMF), and RMS-based refinement.</li><li>A subfolder named <b>Images</b>, which stores the figures generated by six of the seven provided scripts.…”