0000000000451775
AUTHOR
Cornel Gheorghe Boitor
Using the Breeder genetic algorithm to optimize a multiple regression analysis model used in prediction of the mesiodistal width of unerupted teeth
For the prediction of the unerupted canine and premolars mesiodistal size, have been proposed different variants of multiple linear regression equations (MLRE). These are based on the amount of the upper and lower permanent incisors with a tooth of the lateral support. Aim of present study was to develop a method for optimization of MLRE, using a genetic algorithm for determining a set of coefficients that minimizes the prediction error for the sum of permanent premolars and canines dimensions from a group of young people in an area Romania's central city represented by Sibiu. To test the proposed method, we used a multiple linear regression equation derived from the estimation method propo…
Prediction of the mesiodistal size of unerupted canines and premolars for a group of Romanian children: a comparative study
Objectives The aim of the present study was to develop an optimization method of multiple linear regression equation (MLRE), using a genetic algorithm to determine a set of coefficients that minimize the prediction error for the sum of permanent premolars and canine dimensions in a group of young people from a central area of Romania represented by a city called Sibiu. Material and Methods To test the proposed method, we used a multiple linear regression equation derived from the estimation method proposed by Mojers, to which we adjusted regression coefficients using the Breeder genetic algorithm. A total of 92 children were selected with complete permanent teeth with no clinically visible …