Title :
The regression analysis and prediction of Real estate added value based on genetic algorithm
Author :
Zhao, Yanli ; Jia, Shuangshuang
Author_Institution :
Sch. of Manage., Harbin Univ. of Commerce, Harbin, China
Abstract :
Total productive value of Real estate is a crucial part of the Service Industry, which directly affects the value of GDP. It is significant to predict the added value of the total productive value of Real estate, by historical observed data and dynamic regression equations. Compare dynamic regression equations with genetic algorithm to regression equation from exponential regression and linear regression. The predicted results through genetic algorithm method get closer to the true value than the other two methods. Meanwhile, the result also points out the added value of the total productive value of Real estate with genetic algorithms in the next years.
Keywords :
genetic algorithms; regression analysis; dynamic regression equations; exponential regression; genetic algorithm; linear regression; productive value; real estate added value; regression analysis; service industry; Analytical models; Biological system modeling; Computational modeling; Equations; Industries; Mathematical model; Predictive models; egression equation; genetic algorithms; real estate added value;
Conference_Titel :
Management Science and Industrial Engineering (MSIE), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8383-9
DOI :
10.1109/MSIE.2011.5707566
