z-logo
open-access-imgOpen Access
Construction of a Complex System Based on Big Data for the Intelligent Service System of Youth Physical Health
Author(s) -
Xinwen Li,
Chao Song,
Christine A. Rochester,
Chaobing Yan
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/6635346
Subject(s) - service (business) , health management system , plan (archaeology) , service system , computer science , big data , intervention (counseling) , physical health , physical fitness , medical education , knowledge management , psychology , medicine , mental health , marketing , nursing , business , alternative medicine , data mining , physical therapy , archaeology , pathology , psychotherapist , history
The progress of social economy has created a better environment for the healthy development of young people, but the heavy schoolwork and life pressure have caused many students to ignore the scientific management of physical health. At this stage, people need a scientific physical health service system to help students understand their own health data, propose targeted exercise methods and health knowledge, and actively encourage and guide students to participate in physical exercise. The purpose of this article is to cultivate students’ good self-exercise awareness and improve their physical fitness and health. To this end, this article has designed a smart health service system for young people. This article introduces the various service functions in the health management service system and explains in detail the entry, induction, and analysis of student physical health data in the system. The essence of the health intelligent service system is to provide students with targeted healthy exercise strategies through data analysis. This paper studies the health intervention plan of the health intelligent service system. From the experimental data, the improved particle swarm algorithm in this paper increases the effectiveness of the system in adolescent health data mining from 80.5% to 92.19%, which undoubtedly optimizes the system. It helps a lot.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom