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影响房地产价格的因素,有土地使用制度、人口因素、经济发展状况、财政金融政策等的一般因素,本文以房地产价格(主要以住宅价格)为研究对象,以数据挖掘为基础建立房价预测模型,其次用灰理论深入分析并确定了影响房价的主要因素和各自权重,经过分析,确定出影响房价的四个主要因素分别是房地产投资、人均年收入、人口密度、年贷款利率,对房价影响的权重分别是(0.276,0.253,0.244,0.227),然后根据各个因素建立多目标优化房价系统分析合理房价,通过对广州市房地产价格进行定性和定量的研究,得出广州商品房单位房价的合理区间为[6324.6,12694.1],并揭示了其内在的运行机制及提出相关建议。
The factors affecting the real estate price are the general factors such as the land use system, the population factor, the economic development status and the financial and financial policies. Taking the real estate price (mainly the residential price) as the research object and the data mining as the foundation, this article establishes the house price forecasting model, Secondly, with the gray theory, the paper deeply analyzes and determines the main factors affecting the house price and their respective weights. After analyzing, the four main factors affecting the house price are the real estate investment, the annual per capita income, the population density, the annual loan interest rate, the impact on the house price The weights are respectively (0.276,0.253,0.244,0.227), and then build a multi-objective optimization of housing prices based on various factors to analyze the reasonable price, through the qualitative and quantitative research on real estate prices in Guangzhou, the reasonable range of housing prices in Guangzhou real estate [6324.6,12694.1], and revealed its inherent operation mechanism and put forward relevant suggestions.