Real estate price impact factor analysis method combining geographic weighting and multilayer linearity

A technique of geographic weighting and impact factor, applied in the field of geographic information science, which can solve problems such as not considering spatial heterogeneity

Pending Publication Date: 2021-11-09
WUHAN UNIV
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  • Abstract
  • Description
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Similarly, the hierarchical linear model, as a ...

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  • Real estate price impact factor analysis method combining geographic weighting and multilayer linearity
  • Real estate price impact factor analysis method combining geographic weighting and multilayer linearity
  • Real estate price impact factor analysis method combining geographic weighting and multilayer linearity

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Embodiment Construction

[0037] The present invention is mainly based on the basic idea in spatial statistics, combines the geographic weighted regression model and the multi-layer linear regression model, and considers the multi-scale phenomenon and spatial heterogeneity phenomenon in the real estate price influencing factor analysis problem at the same time, so as to provide More reliable and reasonable analysis results of factors affecting real estate prices.

[0038] The method provided by the invention requires computer software technology with manual intervention to carry out. Embodiment The process of the present invention is described in detail by analyzing the influencing factors of second-hand housing prices in Wuhan. The data contains various attribute information (spatial location, average price per square meter, property fee, building area, whether it is a high-rise, etc.) of 19,854 sets of second-hand housing in 795 communities, neighborhood information (distance to the nearest water sys...

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Abstract

The invention provides a real estate price impact factor analysis method combining geographical weighting and multilayer linearity, which comprises the following steps: grouping all real estate project samples according to space coordinates, and classifying the samples in the same area in position into one group; according to the method, classifying real estate attribute variables and related geographic space variables into spatial variables and non-spatial variables, performing variable optimization, obtaining a final model, wherein the final model comprises group-level variables and sample-level variables; constructing a multi-layer linear model by using the sample-level variables and solving the multi-layer linear model; and combining the final solution, and combining the parameters and variables obtained in the previous step to explain dependent variables so as to obtain a real estate price influence factor analysis result. In order to solve a multi-scale phenomenon and a spatial heterogeneity phenomenon in a real estate price impact factor analysis problem, a multi-layer linear regression model and a geographical weighted regression model are combined, and a more reasonable real estate price impact factor analysis result is automatically given.

Description

technical field [0001] The invention belongs to the field of geographic information science, in particular to a method for analyzing factors affecting real estate prices combined with geographic weighting and multi-layer linearity. Background technique [0002] The housing problem is an important issue related to people's livelihood. With the rapid growth of real estate market prices in many places in recent years, this problem has become more serious and has become a topic of extensive discussion among the masses. At present, there are already many real estate information integration and publishing sites on the Internet, such as Fangtianxia and Anjuke. However, these websites usually only provide the release of real estate-related attributes and transaction information, and lack methods to analyze the factors affecting the prices of different real estate projects, so they cannot provide analysis of the distribution of housing prices and the endogenous factors of changes. ...

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/16G06K9/62G06F17/18
CPCG06Q30/0206G06Q50/16G06F17/18G06F18/2431
Inventor 卢宾宾胡奕公
Owner WUHAN UNIV
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