基于混沌理论的沈阳普通商品住宅价格研究

发布时间：2018-01-11 21:19

本文关键词：基于混沌理论的沈阳普通商品住宅价格研究　出处：《沈阳建筑大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着我国房地产市场商品化的发展,房地产行业突飞猛进,为人民的生活提供了应有的保障。房地产市场发展到了今天,已经成为中国经济发展的源泉,成为了所有领域研究与发展的核心。因此,产生了大量的房地产相关专业的学者在房地产市场领域从事调研和研究工作,每一位学者都想尽自己的一份力为房地产市场把把脉,解决房地产市场中存在的复杂问题。混沌理论自从发现以来一直在不停地改变着世界,使得之前很多复杂无序的现象开始变得有章可循、有理可依,所以利用动力学中的混沌理论来研究各个领域都是一种方法和手段的提升,都会为该行业的规范和发展做出贡献。特别是对房地产行业,对我国的房地产市场进行混沌研究,将为这个复杂多变又如此重要的行业发展产生深远的影响。本文首先通过房地产价格构成及影响因素加以探讨、分析,研究房价的波动中的合理与非合理因素,并且结合混沌原理,求出房地产市场价格时间序列的混沌吸引子,证明房地产市场的混沌性特征。其次,对房价预测方法加以介绍和对比,分析各种方法的优缺点,最终选择BP神经网络预测模型应用在沈阳市普通商品房住宅价格时间序列之中。选取matlab软件进行数据的处理与模型的编制工作,通过matlab首先对选取出来影响房地产市场的重要因素的数据进行归一化处理,再建立了一个含有一个输入层、一个隐藏层、一个输出层的三层的简单的BP人工神经预测模型,带入数据,经过其特有的“学习”与“训练”过程得出处理后的数据以及拟合的图形。最后应用模型对沈阳市普通商品房住宅市场价格进行模型仿真,求出模型预测精度,并且与其他模型加以对比,说明在预测房间方面该模型在精度与可操作性方面的优势。再此基础之上,应用模型对沈阳市普通商品住宅价格进行短期预测,得出预测值,希望对沈阳市房价的走势与控制起到一定的作用,为今后该领域学者应用模型及继续研究做好铺垫工作。最终对本文研究中可能存在的问题以及该课题的继续研究工作给出建议与意见。
[Abstract]:With the development of commoditization of real estate market in our country, the real estate industry is advancing by leaps and bounds, which provides the guarantee for the people's life. The real estate market has become the headspring of China's economic development today. Has become the core of all fields of research and development. Therefore, there are a large number of real estate related professionals engaged in research and research in the real estate market. Every scholar wants to do his part to help the real estate market to solve the complex problems existing in the real estate market. Chaos theory has been changing the world since it was discovered. It makes a lot of complex and disordered phenomena become rule-based and rational, so using chaos theory in dynamics to study each field is a method and means to improve. All will contribute to the standardization and development of the industry, especially for the real estate industry, the real estate market in China for chaotic research. This paper will have a profound impact on the development of this complex and such an important industry. Firstly, this paper discusses the composition of real estate price and its influencing factors, and analyzes the reasonable and unreasonable factors in the fluctuation of house price. And based on the chaos principle, the chaotic attractor of the real estate market price time series is obtained to prove the chaotic characteristics of the real estate market. Secondly, the method of house price prediction is introduced and compared. The advantages and disadvantages of various methods are analyzed. Finally, the BP neural network prediction model is selected to be applied in the time series of housing prices in Shenyang. The matlab software is selected to process the data and compile the model. Through matlab, we first normalize the data of the important factors that affect the real estate market, and then establish a hidden layer and an input layer. A simple BP artificial neural prediction model with three layers of output layer is brought into the data. Through its unique "learning" and "training" process to get the processed data and fitting figure. Finally, the model is used to simulate the market price of ordinary commercial housing in Shenyang, and the prediction accuracy of the model is obtained. And compared with other models, the model in the prediction of rooms in the accuracy and maneuverability of the advantages of the model. On the basis of this, the application of the model to Shenyang ordinary commodity housing prices short-term prediction. The prediction value is expected to play a certain role in the trend and control of housing prices in Shenyang. Finally, some suggestions and suggestions are given on the problems that may exist in this study and the continuing research work of this subject.
【学位授予单位】：沈阳建筑大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F299.23

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