Extracting the size from the sizing system table of the humanbody measurements

Abstract

The paper presents the research’s results in extracting the size from the sizing system table of the human body measurements, which has got 24 sizes with 5 kinds of different inside legs from the sample has got 542 men who are living in Southern Vietnam and from 18 to 25 years old. The Principal Component Analysis to choose of the best primary dimensions to design the target function with force conditions and edge conditions. This target function is the function of multiple linear regression models. The mathematical model with input are variables of primary dimensions that are the inside leg measurement and the neck size measurements, these variables values have in the sizing system table. The result is the size need. This model support to look for sizes in the shortest time. Extracting sizes are very useful in the manufacture of garments and business clothing by online, face to face. It will reduce the time to choose the size for fitting body measurements.