Benchmark test functions. by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

Algorithm parameters. by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

DMTD algorithm. by Yunhu Huang (21402795)

Subjects:

Parameters of trained algorithms. by Swathi Anil (17382903)

Pairwise comparisons and significance tests between algorithms for each regression metric. by Shikun Chen (14625352)

MEDOC: A Fast, Scalable, and Mathematically Exact Algorithm for the Site-Specific Prediction of the Protonation Degree in Large Disordered Proteins by Martin J. Fossat (3714079)

Subjects: “…mathematically exact algorithm…”

Compare NC versus the network area using MVO algorithm with different methods in case of 36 mesh routers. by Le Huu Binh (18340233)

Subjects:

Compare NC versus the network area using MVO algorithm with different methods in case of 40 mesh routers. by Le Huu Binh (18340233)

Subjects:

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…In contrast, for smaller and denser systems such as diamond nanoparticles, especially if employing large basis sets, algorithms that use the underlying molecular orbital coefficients offer superior performance, despite their higher formal scaling. …”

A Chemoproteomic Approach for System-Wide and Site-Specific Uncovering of Functional Protein N‑Glycosylation by Guoli Wang (59357)

Subjects:

ANOVA tests for Benchmark functions. by Yu Liu (6938)

“…CEC2021 and 23 benchmark functions are used to test the effectiveness and feasibility of the CTCMKT. …”

The Wilcoxon results for Benchmark functions. by Yu Liu (6938)

“…CEC2021 and 23 benchmark functions are used to test the effectiveness and feasibility of the CTCMKT. …”

Convergence graphs of Benchmark functions. by Yu Liu (6938)

“…CEC2021 and 23 benchmark functions are used to test the effectiveness and feasibility of the CTCMKT. …”

CEC2017 basic functions. by Tengfei Ma (597633)

Subjects:

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

Coarse-fine optimization algorithm. by Chao Ma (207385)

“…The improved gradient extraction method combines the Scale Invariant Feature Transformation (SIFT) algorithm to form a new multi-scale image sharpness evaluation function, SIFT Quad-Tenen. …”