Results of 7 benchmarking functions in 30 dimensions. by M. A. JiMing (19207527)

Parameters setting of function mining experiment. by Jin Ding (11522)

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(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

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Supporting data of the PET image reconstruction using multi-parametric anato-functional priors by Abolfazl Mehranian (11386115)

Power flow and cost optimization with APSO variant-16 of APSO algorithm (a). by Muhammad Ahmad Iqbal (11851338)

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Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

The main steps of the general algorithm. by Dror Mughaz (18017583)

Convergence curve of each DSM algorithms. by Manoj Kumar V. (18196645)

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Multi-functional liquid crystal devices based on random binary matrix algorithm by Tibin Zeng (10890697)

“…Using the new algorithm, several phase-mixing devices were fabricated, and the experiment verified the relationship of the light intensity, polarisation, phase and the algorithm. …”

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning by Bernhard Vennemann (7434353)

“…In this article, we describe how unsupervised novelty detection algorithms can be used to automate the interpretation of blood flow data to improve outcomes through early detection of adverse cardiovascular events without requiring repeated check-ups in a clinical environment. …”

CEC2017 basic functions. by Tengfei Ma (597633)

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Genetic algorithm flowchart. by Junjie He (700642)

“…Then, the epsilon constraint method was used to address the multi-objective model, followed by designing the genetic algorithm based on the problem characteristics for solutions. …”

Our algorithms process large data sets within a minute. by Manu Aggarwal (15990691)

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

Completion times for different algorithms. by Jianbin Zheng (587000)

“…In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

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DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

“…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. …”