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.
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