东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2014, Vol. 35 ›› Issue (8): 1203-1205.DOI: 10.12068/j.issn.1005-3026.2014.08.031

• 资源与土木工程 • 上一篇    下一篇

基于广义回归神经网络的沈阳房地产市场研究

赵亮，王连广，齐锡晶   

  1. (东北大学 资源与土木工程学院， 辽宁 沈阳110819)
  • 收稿日期:2013-11-04 修回日期:2013-11-04 出版日期:2014-08-15 发布日期:2014-04-11
  • 通讯作者: 赵亮
  • 作者简介:赵亮(1976-)，男，辽宁沈阳人，东北大学博士研究生；王连广(1964-)，男，辽宁沈阳人，东北大学教授，博士生导师；齐锡晶(1963-)，男，辽宁沈阳人，东北大学教授.
  • 基金资助:
    住房与城乡建设部科学技术计划项目(2011-R3-27).

Research of Shenyang Real Estate Market Based on Generalized Regression Neural Network

ZHAO Liang， WANG Lianguang， QI Xijing   

  1. School of Resources & Civil Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2013-11-04 Revised:2013-11-04 Online:2014-08-15 Published:2014-04-11
  • Contact: ZHAO Liang
  • About author:-
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摘要： 通过广义回归神经网络对沈阳市房地产市场2003年至2009年相关数据进行训练，采用逼近性最好的光滑因子01，对2010年和2011年的数据进行预测，并与真实数据进行对比，得出沈阳市房地产开发投资额、商品房均价及空置面积均在高位运行.由此判断出沈阳市房地产市场仍处于繁荣期，但属于后期阶段，有出现房地产泡沫的可能，政府、房地产开发商、购房者应给予足够关注.

关键词: 房地产周期, 径向基函数, 广义回归神经网络, 房地产泡沫, 可持续发展

Abstract: Based on the relevant data of Shenyang real estate market from 2003 to 2009， the data from 2010 to 2011 were forecasted using the generalized regression neural network with a smoothing factor of 01 which has excellent approximation， and were compared with the true data. The results show that the developing investment， housing average price， and vacant areas of the real estate in Shenyang are in high level. Moreover， the real estate market is still in the boom， but belongs to the later period. Government， developer， and home buyer should pay attention to the real estate bubbles which may emerge in the future.

Key words: real estate period, radial basis function, generalized regression neural network, real estate bubble, sustainable development

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