ArticleComputational intelligence and neuroscience2022
Prediction and Planning of Sports Competition Based on Deep Neural Network.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed, 6 citations in OpenAlex.
- Artificial Intelligence Program for Predicting Wrestlers' Sports Performances.Sports (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physical education curriculum has been paid more and more attention by teachers and parents, and having a healthy body is the foundation. School sports competition is also more and more concerned by major researchers, and scholars have produced in-depth research and analysis of sports competition results prediction because prediction results can better let teachers carry out appropriate sports training for students, so as to achieve the best learning effect. The construction of the prediction model and whether the performance and universality of the model after construction are suitable for predicting sports competitions have also become a major research point. Deep neural network is a complex network method to analyze the structure of the human brain, which plays a core role in the field of sports planning and performance prediction and can know the future performance of athletes or students in advance in sports competitions. This paper establishes the autoregressive summation model prediction model, the complex neural network prediction model, and the improved complex neural network prediction model. It is concluded that only the improved BP neural network model has a remarkable effect on performance prediction, and the prediction value obtained by this prediction model can reduce the systematic error of prediction, so that it can better infer the performance prediction of sports competitions in China and plan which sports events are suitable for which prediction model.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.