计算机与现代化

• 应用与开发 • 上一篇    

基于ARIMA模型的二手房价格预测

  

  1.  (中国电信股份有限公司广州研究院大数据应用研发中心,广东广州510630)
  • 出版日期:2018-04-28 发布日期:2018-05-02
  • 作者简介:郑永坤(1990),男,广东汕头人,中国电信股份有限公司广州研究院大数据应用研发中心工程师,硕士,研究方向:大数据,机器学习; 刘春(1974),男,高级工程师,硕士,研究方向:大数据,数据挖掘。

Price Prediction of Secondhand House Based on ARIMA Model

  1. (Big Data Application Research and Development Center, Guangzhou Research Institute of 
    China Telecom Co. Ltd., Guangzhou 510630, China)
  • Online:2018-04-28 Published:2018-05-02

摘要:
 摘要: 近年来,我国一二线城市房价持续上涨,房屋成了人们日常生活讨论的热门话题,大家纷纷对未来的房价走势做出猜测。本文爬取国内某知名大型房产网站自2013年以来广州和深圳的二手房均价数据,采用ARIMA模型对未来的房价进行滚动预测,并使用RMSE对预测精度进行判断。结果表明,该模型可以对二手房均价进行持续预测,且预测精度较高,可为房屋买卖者提供参考。

关键词: ARIMA, 房价, 预测, 时间序列

Abstract: In recent years, house prices in China’s firsttier and secondtier cities have continued to rise, and houses have become a hot topic of discussion in daily life, we have to guess the future trend of housing prices. In this paper, we take up the average price of secondhand housing in Guangzhou and Shenzhen since 2013 from a domestic wellknown largescale real estate websites, use the ARIMA model to rollingly forecast the future housing price, and use RMSE to judge the prediction accuracy. The results show that the model can predict the average price of secondhand house continuously, and the prediction accuracy is higher, which can be used as reference for housing traders.

Key words:  ARIMA, housing price, prediction, time series

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