Advancement in real time football analysis using fuzzy based decision-making of the WASPAS method
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a novel fuzzy decision-making framework using circular q-rung orthopair fuzzy sets to enhance football functional strength training analysis. The approach improves expert opinion integration for better real-time football performance insights.
Area Of Science
- Fuzzy mathematics
- Decision science
- Sports analytics
Background
- Football functional strength training requires robust decision-making tools.
- Existing fuzzy sets struggle with uncertainty and vagueness in expert judgments.
- Intelligent picture-processing and deep learning offer potential for football analysis.
Purpose Of The Study
- To develop and assess a novel fuzzy decision-making approach for football functional strength training.
- To introduce circular q-rung orthopair fuzzy sets (Crq-ROFS) for mitigating uncertainty in expert opinions.
- To integrate deep learning and fuzzy logic for advanced football performance analysis.
Main Methods
- Development of circular q-rung orthopair fuzzy set (Crq-ROFS) theory.
- Modification of Dombi power aggregation operators (Crq-ROFDPWA, Crq-ROFDPWG).
- Application of the weighted aggregated sum product assessment (WASPAS) method for multi-attribute group decision-making (MAGDM).
Main Results
- Established novel aggregation operators for integrating expert opinions without external criteria weights.
- Demonstrated the robustness and applicability of the proposed fuzzy framework.
- Successfully applied the WASPAS method to rank alternatives in football analysis scenarios.
Conclusions
- The proposed Crq-ROFS framework effectively handles uncertainty and vagueness in football performance analysis.
- The developed aggregation operators and WASPAS method provide a superior approach compared to existing algorithms.
- This research offers a significant advancement in real-time football analysis and training optimization.
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