摘要
分析房地产价格波动特征可提高价格波动预测能力,因而提出基于大数据分析技术构建房地产价格波动特征模型。构建房地产价格波动的大数据统计分析模型,分析样本后统计结果,根据结果分布式拟合房地产价格波动特征;通过似然估计和二乘拟合算法,跟踪房地产价格波动的曲线,提取房地产价格波动特征;通过模糊信息调度和关联特征挖掘优化特征采样匹配算法,结合市场价格因素预测,得到房地产价格波动特征预测的统计函数,实现房地产价格波动预测。仿真结果表明,此方法对房地产价格波动预测的精度较高,对房地产价格波动特征的优化提取能力较好。
By analyzing the characteristics of real estate price fluctuation,the prediction ability of price fluctuation can be improved.Therefore,this paper puts forward a real estate price fluctuation characteristic model based on big data analysis technology.A big data statistical analysis model of real estate price fluctuation is constructed,the statistical results of the sample are analyzed,and the real estate price fluctuation characteristics are fitted according to the results;the curve of real estate price fluctuation is tracked by likelihood estimation and square fitting algorithm.The statistical function of real estate price fluctuation feature prediction is obtained by fuzzy information scheduling and association feature mining.Real estate price volatility can be forecasted.The simulation results show that the accuracy of the method is high and the ability to optimize and extract the characteristics of real estate price fluctuation is better.
作者
金勇
JIN Yong(Shanghai Greenland Holding Group, Shanghai 200023, China)
出处
《微型电脑应用》
2021年第6期146-149,共4页
Microcomputer Applications
关键词
大数据技术
房地产价格
波动特征
拟合
big data technology
the price of real estate
fluctuation characteristics
fitting
