Predicting human body composition using a modified adaptive genetic algorithm with a novel selection operator.

ABSTRACT:

Background

Changes to human body composition reflect changes in health status to some extent. It has been recognized that these changes occur earlier than diseases. This means that a reasonable prediction of body composition helps to improve model users' health. To overcome the low accuracy and poor adaptability of existing human body composition prediction models and obtain higher efficiency, we proposed a novel method for predicting human body composition which uses a modified adaptive genetic algorithm (MAGA).

Methods

Firstly, since there are many parameters for a human body composition model, and these parameters are associated, we designed a new parameter selection approach by combining the improved RReliefF method with the mRMR method. Following this, selected paramete

SUBMITTER: Gao X 

PROVIDER: S-EPMC7365447 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature