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Research on real estate and its application of refrainingthe speculation

机译:房地产研究及其在抑制炒作中的应用

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Taking Hebei Province as the concrete analysis object, this essay aims to discuss the generally rising house prices in each city. It makes a detailed analysis of the various factors that affect house prices, and draws final conclusions and relevant suggestions. Problem 1: Math models of city house price. Through the analysis of the affecting factors such as urban population, household consumption level, land cost in each region and the number of real estate enterprises, the essay makes a comprehensive discussion, and establishes a multiple linear regression equation model. The expression is: y = 2398915.227 – 1494.917*x1+0.01*x2-625.169*x3 The essay makes a detailed analysis of the formation of house price, evolution mechanism and speculation of real estate through the above linear regression equation. Problem 2: Model of house price evaluation elements. By analyzing the factors from data obtained from Statistical Bureau of Hebei province, the essay finally gets the variable function of each indicator: y1=-0.185*x1-0.029*x2+0.24*x3+0.3.9*x4+0.245*x5+0.274*x6+0.004*x7 y2=0.482*x1+0.0410*x2-0.005*x3-0.153*x4-0.007*x5-1.00*x6+0.370*x7 And it reaches the final comprehensive evaluation model of principle elements: Z = (4.339*y1+1.508*y2)/21.539 Thus, we get the ranking of each factor on house price. Problem 3: The essay uses grey forecasting method to predict the house price in the next few years on the basis of problem 2 and combines the statistic regression math constructed in problem 1, and makes further analysis over each element, thus obtaining the following predictions: Predictions of house price in the year 2010-2013 2010 2011 2012 2013 11957 14139 16720 19772 Finally, the essay gives the policy suggestions over refraining the speculation of real estate on the basis of the above results: (1) The government shall issue related laws and regulations to encourage residents to buy property in the countryside and villages; (2) The supervision over land development shall be strengthened; (3) The increase of population should be controlled; (4) The constraint of laws and policies shall be strengthened.
机译:以河北省为具体的分析对象,这篇文章旨在讨论每个城市的普遍上涨房价上涨。它详细分析了影响房价的各种因素,并得出最终结论和相关建议。问题1:城市房价的数学模型。通过分析城市人口,家庭消费水平,每个地区土地成本等影响因素和房地产企业数量,论文进行了全面的讨论,并建立了多元线性回归方程模型。表达式是:Y = 2398915.227 - 1494.917 * x1 + 0.01 * x2-625.169 * x3本文通过上述线性回归方程详细分析了房价,演化机制和房地产炒作的形成。问题2:房屋价格评估元素的模型。通过分析从河北省统计局获得的数据的因素,本文终于获得了每个指标的可变功能:Y1 = -0.185 * x1-0.029 * x2 + 0.24 * x3 + 0.3.9 * x4 + 0.245 * x5 + 0.274 * x6 + 0.004 * x7 y2 = 0.482 * x1 + 0.0410 * x2-0.005 * x3-0.153 * x4-0.007 * x5-1.00 * x6 + 0.370 * x7并达到原则元素的最终综合评估模型:z = (4.339 * y1 + 1.508 * y2)/21.539因此,我们得到了房价上的每个因素的排名。问题3:论文使用灰色预测方法在未来几年内在问题2中预测房价,并结合了问题1所构成的统计回归数学,并进一步分析每个元素,从而获得以下预测: 2010-2010 2010年2010年2010年2010年2010年2010年2010年2010年2010年2012年2012年11957 14139 16720 19772年,论文赋予了抑制了抑制房地产的策划,以上结果:(1)政府应发出相关法律和法规鼓励居民在农村和村庄购买房产; (2)加强对土地发展的监督; (3)应控制人口的增加; (4)法律和政策的约束应加强。

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