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基于广义回归神经网络的沈阳房地产市场研究
引用本文:赵亮,王连广,齐锡晶.基于广义回归神经网络的沈阳房地产市场研究[J].东北大学学报(自然科学版),2014,35(8):1203-1205.
作者姓名:赵亮  王连广  齐锡晶
作者单位:(东北大学 资源与土木工程学院, 辽宁 沈阳110819)
基金项目:住房与城乡建设部科学技术计划项目(2011-R3-27)
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  

Research of Shenyang Real Estate Market Based on Generalized Regression Neural Network
ZHAO Liang,WANG Lian guang,QI Xi jing.Research of Shenyang Real Estate Market Based on Generalized Regression Neural Network[J].Journal of Northeastern University(Natural Science),2014,35(8):1203-1205.
Authors:ZHAO Liang  WANG Lian guang  QI Xi jing
Institution:School of Resources & Civil Engineering, Northeastern University, Shenyang 110819, China.
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.
Keywords:real estate period  radial basis function  generalized regression neural network  real estate bubble  sustainable development  
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