콘텐츠 본문
논문 해외 국제전문학술지(SCI급) Development of a hierarchical estimation method for anthropometric variables
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2004-09
- 저자명 Heecheon You, Taebeum Ryu
- 학술지명 International Journal of Industrial Ergonomics
- 발행처명 ELSEVIER
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 2
논문 초록 (Abstract)
Most regression models of anthropometric variables use stature and/or weight as regressors; however, these ‘flat’ regression models can produce large errors in estimation for anthropometric variables having low correlations with the regressors. A novel method was proposed which estimates anthropometric variables in a hierarchical manner based on the geometric and statistical relationships between the variables. This hierarchical estimation method first constructs estimation structures by analyzing the dimensional characteristics and geometric relationships of the anthropometric variables and then develops regression models based on the estimation structures. The hierarchical estimation method was applied to 60 anthropometric variables (selected for the design of an occupant package layout in a passenger car) by using the 1988 US Army anthropometric survey data. The hierarchical regression models showed a 55% increase in adjusted R2 and a 31% decrease in SE on average when compared with corresponding flat regression models.
