Journal of University of Chinese Academy of Sciences >
Analysis of construction land by back-propagation neural network model with Xinjiang as a case
Received date: 2009-02-05
Revised date: 2009-03-11
Online published: 2009-07-15
Taking Xinjiang as an example, we establish a predicting model by using BP neural network, and make a prediction of construction land in 2007. The model learning samples are from the social-economic statistical data between 1996 and 2006. The results show that the relative error between the predicted and actual value is only 0.06％, and the BP neural network has higher precision and better effectiveness than traditional methods. Some strategic countermeasures are put forward for sustainable land use in Xinjiang.
Key words： BP neural network model; construction land; influencing factor; prediction; Xinjiang
DUAN Zu-Liang , ZHANG Xiao-Lei , QUAN Xiao-Yan . Analysis of construction land by back-propagation neural network model with Xinjiang as a case[J]. Journal of University of Chinese Academy of Sciences, 2009 , 26(4) : 451 -457 . DOI: 10.7523/j.issn.2095-6134.2009.4.004
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