Uma revisão sistemática da literatura sobre a previsão do desempenho na natação: métodos, conjuntos de dados, técnicas e tendências de investigação
DOI:
https://doi.org/10.47197/retos.v67.112197Palavras-chave:
Previsão, Rede Neural Artificial, Desempenho na Natação, Método, TendênciaResumo
Introdução: Prever o sucesso da natação em desportos de competição, principalmente os resultados de futuras competições olímpicas de natação.
Objectivo: Este artigo fornece uma revisão abrangente e sistemática da investigação sobre a previsão do desempenho na natação publicada entre 2014 e 2024.
Metodologia: A investigação sobre a previsão do desempenho na natação foi realizada através de uma Revisão Sistemática da Literatura (RSL). Além disso, para estabelecer os limites dos artigos de acordo com o tema de investigação, este estudo utilizou as diretrizes PRISMA para conduzir a revisão sistemática. O resultado da extração dos estudos selecionados foi a identificação e análise de 21 publicações científicas que descrevem os temas de investigação, conjuntos de dados, técnicas, métodos, avaliações e problemas nesta área. Resultados: A análise fornece uma explicação detalhada dos temas e tendências que centram os estudos na previsão do desempenho da natação, oferece referências a conjuntos de dados públicos e explica as técnicas e métodos utilizados pelos investigadores.
Discussão: O modelo matemático preditivo é uma técnica popular, pois integra variáveis biológicas e biomecânicas complexas, proporcionando previsões precisas. Além disso, para melhorar a precisão e a interpretabilidade das previsões, é necessário utilizar abordagens híbridas que combinem modelos matemáticos com técnicas mais avançadas, como a aprendizagem automática e a inteligência artificial explicável (XAI).
Conclusões: A previsão do desempenho da natação é essencial para melhorar os programas de treino, orientar a seleção dos atletas e avaliar o seu progresso.
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