【作者】 高毛毛；

【导师】 杨建平；

【作者基本信息】 西安建筑科技大学 ， 技术经济及管理， 2008， 硕士

【摘要】 近年来,住宅业被确立为新的经济增长点和消费热点,发展迅速。而最受人们瞩目的要属其价格,尤其随着近年来全国各地房价不断上涨,房地产价格成为房地产市场的任何主体都讨论的热点。因此,如何科学地运用房价这一无形的指挥棒来调控住宅市场,保障城市住宅市场健康、稳定、有序发展,促进宏观经济的稳定健康运行,已成为社会各界所关注的问题。本研究在分析国内外经济预警及房地产市场预警研究成果的基础上,提出本论文主要应用人工神经网络预测法进行普通商品住宅价格预警研究。因此论文首先对人工神经网络的理论进行简要分析,随后提出本文研究的主要对象普通商品住宅,在对其概念、价格内涵、价格特征及形成机制进行详细分析的基础上讨论影响普通商品住宅价格的因素,并通过详细论证选择相应因素的指标且进行相关分析对这些指标进行筛选,建立了普通商品住宅价格影响因素指标体系。然后,在此基础上选择预警指标,建立影响合理价格因素的指标体系,并应用人工神经网络对其进行预测,通过与市场价格的比较对普通商品住宅价格波动进行实时监测预警。最后,本文以西安市为例进行普通商品住宅价格预警的实证研究,并根据结论进行西安市普通商品住宅价格预警分析,结果是目前西安市普通商品住宅价格水平合理,与其社会经济发展水平相适应且房价水平将继续稳步攀升,短期内不会有大的波动。更多还原

【Abstract】 In recent years, the domestic industry was established as a new economic growth point and consumption hot spots, is developing rapidly. And to the attention of most people is their prices, especially in recent years throughout the country as rising house prices, real estate prices into the real estate market of any of the main hot spots are discussed. Therefore, how to use science to the price of this invisible baton to control the housing market, protection of urban housing market healthy, stable and orderly development, and promote the healthy operation of macroeconomic stability, has become a community concern.In this study the analysis of domestic and international economic early warning and the real estate market on the basis of research results, the main thesis of the present application of artificial neural network forecasting method general warning on house prices of goods. So the first papers on artificial neural network theory brief analysis, followed by this paper, the main target of ordinary commercial housing, its concept, content prices, features and price formation mechanism for detailed discussions on the basis of the analysis of the impact of commodity housing price factor And, through detailed feasibility studies of the factors select the appropriate indicators and related analysis of these indicators of screening, a general merchandise domestic factors affect the price index system. Then, on the basis of this choice of early warning indicators, the impact of the establishment of a reasonable price index system and its application of artificial neural networks to predict, by comparison with the market price of the commodity price fluctuations in residential real-time monitoring of early warning. Finally, to Xi’an as an example for ordinary residential commodity prices early warning of empirical research and conclusions based on domestic commodity prices in Xi’an early warning analysis, Xi’an is the result of ordinary commercial housing price level reasonable, rather than the level of socio-economic development And the level of house prices will continue to steadily rise, the short term there will be no major fluctuations.更多还原