Open AccessResearch and analysis of maximum likelihood recursive identification algorithm based on physical exercise behavior of obese children
Author(s) -
Huoping Zhao,
Dong Wang,
Dahu Li,
Kang Sun,
Wanjun Zhang,
Xiaoping Gou,
Feng Zhang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/714/3/032042
Subject(s) - identification (biology) , matlab , maximum likelihood , computer science , psychology , algorithm , physical therapy , mathematics , machine learning , statistics , medicine , botany , biology , operating system
With the decrease of physical activity, children’s health problem will become an urgent problem in building a well-off society in an all-round way. There are differences in the safe heart rate of children with different physique when they exercise.This paper studies the suitable heart rate of children with different physique. Based on a maximum likelihood recursive algorithm for obese children’s physical exercise behavior, a model recognition system based on the maximum likelihood recursive algorithm for obese children’s physical exercise behavior is established. Finally, through MATLAB simulation analysis, the results show that fat the model recognition of MLR algorithm is consistent with the actual results, and the simulation results verify the feasibility and effectiveness of MLR algorithm.