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›› 2009, Vol. 26 ›› Issue (4): 451-457.DOI: 10.7523/j.issn.2095-6134.2009.4.004

• Research Articles • Previous Articles     Next Articles

Analysis of construction land by back-propagation neural network model with Xinjiang as a case

DUAN Zu-Liang1,2, ZHANG Xiao-Lei1, QUAN Xiao-Yan1,2   

  1. 1. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
    2. Graduate University of the Chinese Academy of Sciences, Beijing 100049, China
  • Received:2009-02-05 Revised:2009-03-11 Online:2009-07-15

Abstract:

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

CLC Number: