Curves of sigmoid functions used in our proposed algorithm. by Binh Thanh Dang (12368831)

“…<p>Curves of sigmoid functions used in our proposed algorithm.</p>…”

CEC2017 basic functions. by Tengfei Ma (597633)

Subjects:

MATLAB codes for Optimization of General Aviation Aircrafts Wing Design to Achieve the Optimal Range and Meet Performance Requirements Using Non-Dominated Sorting Genetic Algorithm... by Amirreza Zibafar (9980246)

“…<p>I worked on project titled '' Optimization of General Aviation Aircrafts Wing Design to Achieve the Optimal Range and Meet Performance Requirements Using Non-Dominated Sorting Genetic Algorithms II'' previously and wanted to make this useful to others by sharing it's codes. …”

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. …”

The <i>FSIM</i> results for all algorithms. by Zihao Wang (845023)

“…To demonstrate the effectiveness of the proposed algorithm, we use the CEC2022 benchmark function test suite to perform comparison experiments. the HGJO is compared with the original GJO and five classical meta-heuristics. …”

The <i>SSIM</i> results for all algorithms. by Zihao Wang (845023)

“…To demonstrate the effectiveness of the proposed algorithm, we use the CEC2022 benchmark function test suite to perform comparison experiments. the HGJO is compared with the original GJO and five classical meta-heuristics. …”

The <i>PSNR</i> results for all algorithms. by Zihao Wang (845023)

“…To demonstrate the effectiveness of the proposed algorithm, we use the CEC2022 benchmark function test suite to perform comparison experiments. the HGJO is compared with the original GJO and five classical meta-heuristics. …”

Algorithm parameter settings. by Tao Dong (15551)

“…In the scheduling of combined heat and power systems, the competing goals of economic cost and pollutant emission are challenging for conventional single-objective algorithms to handle, necessitating the use of effective multi-objective optimization algorithms. …”

The used test functions in the evaluation. by Xuan Chen (158617)

Algorithm used for important sampling of the likelihood function. by Zhiyong Huang (3620000)

Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance by Xuejun Yu (631893)

“…Checking for uniformity when a posterior density is approximated numerically provides a diagnostic for algorithm validity. Furthermore, adjustments to achieve uniformity can improve the quality of approximate inference methods. …”

Benchmark test functions. by Sinan Q. Salih (8877938)

“…The method formulated was subjected to testing using a set of nine widespread and popular benchmark test functions. …”

Performance validation of different algorithms in two benchmark functions. by Wenjing Wang (181404)

Subjects:

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

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

“…Leveraging the sequences within the flavodoxin-like subdomain, we developed a substrate specificity prediction algorithm using a protein language model, achieving 92% overall prediction accuracy for 43 frequently observed amino acids, significantly improving the prediction reliability. …”

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

“…To address this issue, most metaproteomics tools rely on the lowest common ancestor (LCA) algorithm to assign biological functions, which often leads to incomplete biological function assignments across the full taxonomic lineage of identified microorganisms. …”

The set of Pareto solutions. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Flowchart of LLSKSO. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

The case of LLSKSO with the value of the weight coefficient <i>w</i> in steps of 0.1. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”