| 引用本文： |
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邝文竹,刘琳.南宁市二手房价格影响因素分析及房价走势的预测[J].广西科学院学报,2012,28(2):110-112. [点击复制]
- KUANG Wen-zhu,LIU Lin.Analysis and Prediction of the Factors That Influence the Price of the Second-hand House in Nanning[J].Journal of Guangxi Academy of Sciences,2012,28(2):110-112. [点击复制]
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| 摘要: |
| 选择南宁市江南区、西乡塘区、青秀区以及兴宁区的二手房销售数据,以地理因素为例,运用方差分析和Fisher最小显著差异法研究南宁市二手房售价的影响因素,并用回归分析和BP神经网络预测与其它城区有显著差异的城区的二手房售价随房龄变化的情况。结果发现,西乡塘区和江南区二手房平均售价的均值无显著差异(P>0.05),青秀区二手房平均售价的均值与江南区、西乡塘区、兴宁区的有显著差异(P<0.05),均值差分别为0.23000、0.24310、0.08553,地理因素对二手房价格有显著影响,青秀区的二手房平均售价在4个城区中是最高的,房价随房龄的增加,呈不规则变化。 |
| 关键词: 房价 回归分析 BP神经网络 |
| DOI： |
| 投稿时间：2011-05-24修订日期：2011-07-09 |
| 基金项目:国家自然科学基金项目(11061002)和广西自然科学基金项目(2012GXNSFBA053010)资助。 |
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| Analysis and Prediction of the Factors That Influence the Price of the Second-hand House in Nanning |
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KUANG Wen-zhu, LIU Lin
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| (Department of Mathematics and Information Science, Guangxi University, Nanning, Guangxi, 530004, China) |
| Abstract: |
| According to the study of second-hand house sale data with taking geography factors as sample, by variance analysis and Fisher least significant difference method,the factors that influence the price of second-hand house in Jiangnan,Xixiangtang,Qingxiu and Xingning districts are studied. The regression analysis and BP neural network are used to predict the relationship of second-hand house price changes with the house age.The method is valuable for reference and the research results are based on the facts. |
| Key words: house price regression analysis BP neural network |
