江汉大学学报(自然科学版) ›› 2020, Vol. 48 ›› Issue (2): 10-13.doi: 10.16389/j.cnki.cn42-1737/n.2020.02.002

• 数学 • 上一篇    下一篇

基于GM(1,1)模型的南京市房价预测研究

李广胜,郭欢*   

  1. 江汉大学 数学与计算机科学学院,湖北 武汉 430056
  • 发布日期:2020-04-22
  • 通讯作者: 郭欢
  • 作者简介:李广胜(1995— ),男,硕士生,研究方向:灰色系统。
  • 基金资助:
    国家自然科学青年基金资助项目(71601085);中国博士后面上基金资助项目(2016M601808)

Research on Nanjing City House Price Forecast Based on GM(1,1)Model

LI Guangsheng,GUO Huan*   

  1. School of Mathematics and Computer Science,Jianghan University,Wuhan 430056,Hubei,China
  • Published:2020-04-22
  • Contact: GUO Huan

摘要: 以中国指数研究院发布2018.04-2018.09 南京市房价样本均价数据作为研究对象,并运用GM(1,1)模型,对南京市2018.10-2018.12 房价进行预测并分析。结果表明:GM(1,1)模型的拟合值和预测值均接近于实际值,相对误差率较低,且预测效果优于BP 神经网络模型,为促进房地产行业朝着更好的方向发展提供有利指导。

关键词: GM(1,1)模型, BP神经网络模型, 灰色系统, 南京市, 房价预测

Abstract: Taking data of average price of house price sample in Nanjing released by China Index Research Institute in Apr. 2018 to Sep. 2018 as the research object ,and using GM (1,1)model,to forecast and analyze the housing price of Nanjing in Oct. 2018 to Dec. 2018. The results showed that the GM(1,1) model′s fitting values and predicted values were close to the actual values,the relative error rate was low,and the prediction effect was better than that of BP neural network model. The research provides beneficial guidance for better development of real estate industry.

Key words: GM(1,1) model, BP neural network model, grey system, Nanjing City, house price forecast

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