Specific information on the 7 benchmark functions. by M. A. JiMing (19207527)

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. by Alexis M. Thornton (11068403)

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Flowchart of DQN algorithm. by Jiandong Qiu (20389944)

Comparison of different algorithms. by Jiandong Qiu (20389944)

Objective function values of each algorithm for solving large-scale problems. by Lijun Fan (2007628)

Performance comparison of algorithms in ZDT5 and ZDT6 function tests. by Tao Dong (15551)

Comparison of algorithm performance in ZDT3 and ZDT4 function tests. by Tao Dong (15551)

Comparison of algorithm performance in ZDT1 and ZDT2 function tests. by Tao Dong (15551)

Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

GELU function. by Yuanzhou Zheng (15195249)

Output results based on three algorithms. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

The proposed spherical registration algorithm between macaque and human hemisphere. by Haewon Nam (4102705)

“…<p>For each iteration of the proposed algorithm, curvature, sulcus depth, myelination, node degree, and six group principal components based on functional connectivity matrix were generated and used in the demons registration.…”

Properties of the benchmark functions. by Muhammad Zubair Rehman (11243478)

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Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function. by Davut Izci (15927452)

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Penalty functions and estimators for some of the regularized regression methods used in this paper. by Dongsheng Li (222712)

Comparison of different algorithms. by Dawei Wang (471687)

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3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

Circulatory system-based optimization algorithm with dynamic penalty function for optimum design of large-scale water distribution networks by Veli Batmaz (20800175)

“…To address this challenge, a novel method called circulatory system-based optimization (CSBO) is proposed, which minimizes the need for algorithm-specific parameters and achieves optimal designs across WDNs of various scale. …”