基于模糊聚类分析的房地产评估比较法研究

Research on Comparative Method of Real Estate Appraisal Based on Fuzzy Clustering Analysis

比较法是目前最常用的房地产估价方法,但在实际应用中选取可比实例的随意性较大,因此必然影响结果的准确性。为了尽可能地提高可比实例选取的精确性,本文以深圳市某区域楼盘数据为基础,引入聚类分析统计学方法对比较法进行改进,以提高比较法估价结果的准确性。本研究收集整理了大量与房地产价格有关的数据,在特征因素确定的基础上,通过模糊聚类分析法对有关楼盘数据进行计算并得到最优聚类,进而选出与待估房地产最贴近的可比实例集合。最后,对选取的可比实例的区位状况和实物状况与待估房地产因素进行比较,根据择近原则,将贴近度最大的三个交易实例确定为可比实例。通过将定性分析问题转化为定量分析问题,避免可比实例选择的随意性和特征因素修正的主观性,让比较法改进后的估价结果精确度提高,得到更科学合理的房地产估价结果。

Comparison method is used in Real Estate valuation method commonly,however,the selection of comparable property is relatively random in practical application,and it affects the accuracy of the results inevitably.In order to improve the accuracy of the selection of comparable property,based on the real estate data in a certain area of Shenzhen,this study introduces the fuzzy clustering analysis to improve the comparison method,so as to improve its accuracy.Based on collecting a large number of real estate prices data and the determining characteristic factors,the fuzzy clustering analysis method can be used to calculate the relevant real estate data and get the optimal clustering,then we can select the closest comparable property with the subject property.Finally,the location and physical conditions of comparable properties are compared with the subject property.According to the principle of proximity selection,the three transaction instances with the largest closeness degree are identified as comparable property.By transforming qualitative problems into quantitative problems,it can avoid the arbitrariness of the selection of comparable property and the subjectivity of feature factor modification,to improve the accuracy of the appraisal results after the improvement of the comparative method and to get more scientific and reasonable real estate appraisal results.