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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
2,446 datasets
A benchmark evaluation of 35 soft decision-making algorithms based on fuzzy parameterized fuzzy soft matrices (fpfs-matrices). The study uses the FPFS-CMC classifier to rank algorithms across ten datasets from the UCI Machine Learning Repository, assessing performance with metrics like accuracy, precision, recall, specificity, and F1-score. The dataset, created by Ömer Karakoç and last updated in May 2026, provides the comparative results in an XLS file.
35 soft decision-making (SDM) algorithms based on fuzzy parameterized fuzzy soft matrices (fpfs-matrices) were benchmarked across ten datasets from the UCI Machine Learning Repository. The evaluation, conducted by Ömer Karakoç and last updated in May 2026, used metrics like accuracy, precision, recall, specificity, and F1-score, with statistical significance confirmed via Friedman and Nemenyi tests. The dataset, shared under a CC-BY-4.0 license, identifies top-performing algorithms such as A19 and YHX14.
Ömer Karakoç published a study on 2026-05-13 evaluating 35 soft decision-making algorithms based on fuzzy parameterized fuzzy soft matrices. The research benchmarks these algorithms across ten datasets from the UCI Machine Learning Repository using metrics like accuracy, precision, recall, specificity, and F1-score. Statistical significance was confirmed using Friedman and Nemenyi tests.
Yearly snow melt onset dates over Arctic sea ice derived from SMMR, SSM/I, and SSMIS satellite brightness temperature measurements. The data are gridded to a 25 km Northern Hemisphere Polar Stereographic projection and include value-added statistics for each grid cell, such as mean, earliest, latest, range, and standard deviation of melt onset dates. One browse image is provided for each yearly file and statistical field.
A supplementary dataset of simulation results for capillary fiber-based refractometer sensitivity. It contains approximately 40,150 absolute sensitivity values across a 4D parametric space of cone angle, collapsed length, and sensing medium refractive index. The data was authored by Ardi Rahman and last updated in April 2026.
A 73.1 MB repository of data and scripts for analyzing courtship ultrasonic vocalizations (USVs) in male mice. The dataset includes raw data, R scripts, and rendered HTML reports to reproduce the analyses from the manuscript "Linking Quantity and Acoustic Properties of Courtship Vocalizations in Male Mice" by Kono and Kanno. The repository was last updated on May 4, 2026.
Statistics from the Quebec public service cover aspects of workplace health including prevention management, conflict resolution, employee assistance programs, disability management, and retention. The data is published by the Government and Municipalities of Québec under a CC-BY-4.0 license and was last updated on April 17, 2026.
A 222-byte text report from 2026 summarizing the validation of harmonized TCGA Lower Grade Glioma datasets. The report confirms the structure, consistency, and completeness of final clinical, expression, copy number alteration, and mutation datasets. It was generated by Aaliah Aly using a script named report.py.
229 Brazilian first-grade students participated in a study assessing the selective impact of math anxiety on symbolic versus nonsymbolic mathematical skills. The dataset, authored by Angélica Polvani Trassi and last updated in April 2026, contains supplementary material for the research paper. It includes results from assessments of math anxiety, mathematical skills, nonverbal reasoning, and language abilities.
A supplementary document from a study investigating the selective impact of math anxiety on mathematical skills in first-grade students. The study involved 229 Brazilian first graders from 10 public schools, assessing symbolic and nonsymbolic math skills, math anxiety, and other cognitive measures. The document was authored by Angélica Polvani Trassi and last updated in April 2026.
A 2026 study by Angélica Polvani Trassi investigates the selective impact of math anxiety on symbolic versus nonsymbolic mathematical skills in first-grade children. The dataset likely contains assessment results for 229 Brazilian first-grade students, including measures of math anxiety, mathematical skills (Zareki-R), nonverbal reasoning, and language skills. The file is a 660.8 KB DOCX document published on figshare under a CC-BY-4.0 license.
229 Brazilian first-grade students participated in a study examining the selective impact of math anxiety on symbolic versus nonsymbolic mathematical skills. The dataset, authored by Angélica Polvani Trassi and last updated in April 2026, likely contains assessment scores for math anxiety, number sense, calculation, and other cognitive measures. Results indicate math anxiety correlated with lower performance in symbolic skills like number production and comprehension, but not with number sense or calculation.
Australian Department of Home Affairs data on Visitor visas granted, released quarterly. The de-identified statistics include dimensions for financial year, quarter, month, client location, citizenship country, and visa subclass. The dataset was republished in 2024 following a privacy review and risk assessment.
Sensor data from 2008 to 2022, collected by the IMOS Wireless Sensor Networks Facility across multiple reefs in the Great Barrier Reef. The Australian Ocean Data Network manages this network, which provides real-time, spatially dense measurements of marine conditions. The facility's funding ceased in June 2022, with some sites decommissioned or transferred to the Australian Institute of Marine Science.
A 1.1 MB Excel file containing data for each figure from the NMR-Solver project. The full experimental dataset is publicly accessible via Zenodo. Yongqi Jin authored this dataset, which was last updated on 2026-05-28.
A dataset presenting detection performance metrics with statistical validation using 5-fold cross-validation. The results are reported as mean values with standard deviations. The dataset was authored by Adel Alshamrani and last updated on June 2, 2026.
A 9.5 KB dataset supporting a study on emergency scheduling for high-speed rail logistics disruptions. It was created by Shuaixin Guo and last updated on 2026-04-28. The data likely contains parameters and results for validating a Mixed-Integer Linear Programming model and an Adaptive Large Neighborhood Search algorithm.
A distance matrix likely for nodes in a high-speed rail logistics network, used to model emergency truck transshipment after disruptions. The dataset was created by Shuaixin Guo and last updated on April 28, 2026. It is a small file of 5.5 KB, stored in XLS format.
A 5.5 KB dataset by Shuaixin Guo, last updated April 28, 2026, containing random instance configurations used to validate an emergency scheduling optimization framework for high-speed rail logistics. The data supports a Mixed-Integer Linear Programming model and an Adaptive Large Neighborhood Search algorithm designed for truck transshipment following network disruptions. It was used in a case study of the Zhengzhou-Qingdao Express Rail Line.
Geoscience Australia Data published a simulation experiment in 2026 comparing statistical and mathematical techniques for predicting seabed mud content. The study used samples from the Geoscience Australian Marine Samples database, applied data quality control, and assessed five factors affecting interpolation accuracy across different Australian regions. Outcomes can be applied to modeling physical properties for improved marine biodiversity prediction.