Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm
The mining and analysis of student achievement data is of great importance to teaching management. Using the relevant data of college students’ physical fitness test and sports performance as the object of research, a BP neural network model is developed to predict performance. Based on BP neural ne...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Multimedia |
| Online Access: | http://dx.doi.org/10.1155/2022/1701687 |
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| _version_ | 1832555171908943872 |
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| author | Zhanju Ma Yao Wang |
| author_facet | Zhanju Ma Yao Wang |
| author_sort | Zhanju Ma |
| collection | DOAJ |
| description | The mining and analysis of student achievement data is of great importance to teaching management. Using the relevant data of college students’ physical fitness test and sports performance as the object of research, a BP neural network model is developed to predict performance. Based on BP neural network, an algorithm for predicting students’ endurance performance is proposed, which is applied to the sunshine long-distance intelligent sports testing system at Hangzhou Dianzi University. The nonlinear relationship between students’ performance in sunshine running and endurance performance is determined, and students’ performance in sunshine running is used to predict their endurance performance the following year. Experimental results indicate that the accuracy of the model is above 85%. At the same time, the prediction results are combined with the Internet of things technology to produce a student sports prescription management system, which sets different sunshine running parameters for students with different predicted results and provides personalized sports prescriptions for students with different physical conditions, which has extensive and far-reaching application value. |
| format | Article |
| id | doaj-art-2d2ee2b156ae4c38a74b71b275d4aa7d |
| institution | Kabale University |
| issn | 1687-5699 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Multimedia |
| spelling | doaj-art-2d2ee2b156ae4c38a74b71b275d4aa7d2025-02-03T05:49:22ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/1701687Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network AlgorithmZhanju Ma0Yao Wang1Basic Teaching Department of HebeiSports Department of CangzhouThe mining and analysis of student achievement data is of great importance to teaching management. Using the relevant data of college students’ physical fitness test and sports performance as the object of research, a BP neural network model is developed to predict performance. Based on BP neural network, an algorithm for predicting students’ endurance performance is proposed, which is applied to the sunshine long-distance intelligent sports testing system at Hangzhou Dianzi University. The nonlinear relationship between students’ performance in sunshine running and endurance performance is determined, and students’ performance in sunshine running is used to predict their endurance performance the following year. Experimental results indicate that the accuracy of the model is above 85%. At the same time, the prediction results are combined with the Internet of things technology to produce a student sports prescription management system, which sets different sunshine running parameters for students with different predicted results and provides personalized sports prescriptions for students with different physical conditions, which has extensive and far-reaching application value.http://dx.doi.org/10.1155/2022/1701687 |
| spellingShingle | Zhanju Ma Yao Wang Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm Advances in Multimedia |
| title | Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm |
| title_full | Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm |
| title_fullStr | Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm |
| title_full_unstemmed | Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm |
| title_short | Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm |
| title_sort | analysis and prediction of body test results based on improved backpropagation neural network algorithm |
| url | http://dx.doi.org/10.1155/2022/1701687 |
| work_keys_str_mv | AT zhanjuma analysisandpredictionofbodytestresultsbasedonimprovedbackpropagationneuralnetworkalgorithm AT yaowang analysisandpredictionofbodytestresultsbasedonimprovedbackpropagationneuralnetworkalgorithm |