Data-driven decision-making for enhancing aerobic and anaerobic performance in runners

Abstract

The ability to undertake aerobic and anaerobic activities is critical for runners since these activities have an impact on endurance, speed, and overall performance. The capacity for aerobic exercise allows for prolonged effort throughout long runs, whereas the power of anaerobic exercise allows for rapid bursts of speed and efficient recovery. This article presents a data-driven decision-making technique that incorporates a cubic set with a q-rung Orthopair fuzzy set called cubic q-rung Orthopair fuzzy set (Cq-ROFS) to investigate the aerobic and anaerobic performance of runners. An introduction to Cq-ROFS is provided first, followed by its definition. Secondly, we suggest the Cq-ROF weighted average operator as a means of efficiently aggregating Cq-ROF information. Third, in order to determine the weights of attributes, a Cq-ROF-criterion impact loss method is built. The Cq-ROF-weighted aggregated sum product assessment method is then developed for the purpose of measuring runners’ aerobic and anaerobic performance. In the end, we use comparative analysis to show how our proposed strategy is superior to others.