基于麻雀搜索优化SVR模型的房地产价格研究  

Research on Real Estate Price Index Based on Sparrow Search Optimization SVR Model

作　　者：兰瑞杰 孟维高 耿进强 LAN Ruijie;MENG Weigao;GENG Jinqiang(School of Urban Geology and Engineering,Hebei GEO University,Shijiazhuang 050031,China)

机构地区：[1]河北地质大学城市地质与工程学院,河北石家庄050031

出　　处：《电子科技》2024年第1期1-8,共8页Electronic Science and Technology

基　　金：河北省社会科学基金(HB18GL021)。

摘　　要：为解决传统经济指标作为房价影响因素的数据获取滞后性问题以及机器学习模型在预测房价时存在的参数选取不确定性问题,文中以网络搜索数据作为房价指数解释变量,采用麻雀搜索算法(Sparrow Search Algorithm,SSA)建立SSA-SVR(Support Vector Regression)模型对SVR的惩罚因子C和RBF(Radical Basic Function)核函数的参数g进行优化。将SSA-SVR模型与PSO(Particle Swarm Optimization)-SVR、GA(Genetic Algorithm)-SVR、WOA(Whale Optimization Algorithm)-SVR、GS(Grid Search)-SVR以及基准SVR进行对比,SSA-SVR的相关系数(0.99)、均方根误差(6.71)、平均绝对误差(5.24)、均方误差(45.13)以及平均绝对百分比误差(0.26%)均优于其他5种模型。结果表明,麻雀搜索算法优化的SVR模型在房价预测方面具有更好的全局寻优能力,可以提高模型的预测准确度和预测能力。In order to solve the data acquisition lag problem of traditional economic indicators as an influencing factor of housing prices,and the uncertainty of parameter selection in the machine learning model when predicting housing prices,the network search data is used as the explanatory variable of the house price index,and Sparrow Search Algorithm(SSA)is used to establish the SSA-SVR(Support Vector Regression)model to optimize the penalty factor C of SVR and the parameter g of the RBF(Radical Basic Function)kernel function in this study.Comparison among the established SSA-SVR model with PSO(Particle Swarm Optimization)-SVR,GA(Genetic Algorithm)-SVR,WOA(Whale Optimization Algorithm)-SVR,GS(Grid Search)-SVR and benchmark SVR show that the correlation coefficient of SSA-SVR(0.99),root mean square error(6.71),mean absolute error(5.24),mean square error(45.13)and mean absolute percentage error(0.26%)are better than those of the other five models.The results show that the SVR model optimized by the sparrow search algorithm has better global optimization ability in housing price prediction,which can improve the prediction accuracy and prediction ability of the model.

关 键 词：麻雀搜索算法 优化算法 SVR模型 数据滞后性 参数不确定性 网络搜索数据 房地产价格指数 房价预测 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]