Prediction of College Students’ Physical Fitness Based on K-Means Clustering and SVR-Reference-Cited by-同舟云学术

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Prediction of College Students’ Physical Fitness Based on K-Means Clustering and SVR

Published:2020 Issue:4 Volume:35 Page:237-246
ISSN:0267-6192
Container-title:Computer Systems Science and Engineering
language:en
Short-container-title:

Author:

Tang Peng,Wang Yu,Shen Ning

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

General Computer Science,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.techscience.com/csse/v35n4/40094/pdf

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Waste heat recovery in iron and steel industry using organic Rankine cycles;Chemical Engineering Journal;2023-12

2. Clusters of Success: Unpacking Academic Trends with K-Means Clustering in Education;VFAST Transactions on Software Engineering;2023-11-14

3. A Review of Clustering Models in Educational Data Science Toward Fairness-Aware Learning;Educational Data Science: Essentials, Approaches, and Tendencies;2023

4. Determination of optimum organic Rankine cycle parameters and configuration for utilizing waste heat in the steel industry as a driver of receive osmosis system;Energy Reports;2021-11

5. Artificial Intelligence System for College Students’ Physical Fitness and Health Management Based on Physical Measurement Big Data;Wireless Communications and Mobile Computing;2021-09-20

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