基于居住属性的郑州市商品住宅需求量预测研究
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摘要
基于郑州商品住宅市场2000～2017年数据,构建多元逐步回归模型和等维灰数递补GM(1,1)模型,并用规划求解得出二者的最优组合权重为0.246和0.754。进一步构建最优组合权重-Markov转移模型,预测结果显示:2018～2020年郑州市房屋居住面积分别为27085.763万m~2、29142.119万m~2和31277.411万m~2,且一阶差分衡量年度商品住宅需求量分别为:2355.982万m~2、2056.356万m~2和2135.292万m~2。
Based on the data from Zhengzhou commodity residential market 2000～2017,the paper builds the multivariate stepwise regression model and GM(1,1)model with equidimensional grey number,and obtains the optimal combination weights of 0.246 and 0.754. Further constructs the optimal combined weightMarkov transfer model. The forecasting results show that the residential area in Zhengzhou from 2018 to2020 is 27085.73.63 million m~2,29142.119 million m~2,and 31277.41 million m~2,and the annual demand for goods measured by ? rst order difference is 235.98 million m~2,20563.56 million m~2 and 2135.29 million m~2.
Based on the data from Zhengzhou commodity residential market 2000～2017,the paper builds the multivariate stepwise regression model and GM(1,1)model with equidimensional grey number,and obtains the optimal combination weights of 0.246 and 0.754. Further constructs the optimal combined weightMarkov transfer model. The forecasting results show that the residential area in Zhengzhou from 2018 to2020 is 27085.73.63 million m~2,29142.119 million m~2,and 31277.41 million m~2,and the annual demand for goods measured by ? rst order difference is 235.98 million m~2,20563.56 million m~2 and 2135.29 million m~2.
引文
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[4]涂国平,黄志钧.基于系统动力学的商品住宅需求仿真研究——以南昌市为例[J].华东理工大学学报(社会科学版),2012(6):62-68.
[5]高聚辉.当前住房市场现状分析与前景展望[J].中国发展观察,2015(2):48-54.
[2]中国指数研究院.未来五年(2016-2020)中国房地产市场趋势展望[J].中外建筑,2016(3):24-28.
[3]杨怡.销量的多因素灰色预测和马尔柯夫链模糊修正模型研究[J].工业工程与管理,2014(5):90-93.
[4]涂国平,黄志钧.基于系统动力学的商品住宅需求仿真研究——以南昌市为例[J].华东理工大学学报(社会科学版),2012(6):62-68.
[5]高聚辉.当前住房市场现状分析与前景展望[J].中国发展观察,2015(2):48-54.