Body Fat Percentage Prediction Using Intelligent Hybrid Approaches
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-01
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Excess of body fat often leads to obesity.
Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes.
Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health.
Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs.
Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP.
Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP.
The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques.
The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables.
In the second stage, the remaining important variables are served as inputs for the other forecasting methods.
A real dataset was used to demonstrate the development of the proposed hybrid models.
The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.
American Psychological Association (APA)
Shao, Yuehjen E.. 2014. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049409
Modern Language Association (MLA)
Shao, Yuehjen E.. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1049409
American Medical Association (AMA)
Shao, Yuehjen E.. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049409
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049409