Dataset Karate
Published: 10 February 2026| Version 1 | DOI: 10.17632/y84nxw853r.1
Contributor:
Daniela Martinez PorteDescription
Analysis of the duration of karate tournaments
Files
Steps to reproduce
Logistics Optimization WorkflowData Cleaning: Filter out inactive categories (num_competidores == 0) to focus on active logistics flows.Efficiency Metrics: Calculate the Logistics Efficiency Index to quantify time deviations.Bottleneck Identification: Conduct a Pareto Analysis by modality (Kata/Kumite) to isolate categories responsible for 80% of cumulative delays.Capacity Modeling: Use regression to correlate the number of matches with actual time spent, creating a predictive model for "Load vs. Capacity."Dynamic Rescheduling: Implement calculated "time buffers" into future schedules to minimize athlete wait times and optimize tatami usage.
Institutions
- Universidad de Las AméricasPichincha, Quito
Categories
Artificial Intelligence, Statistical Prediction