经济系统灰色突变预测模型及其应用研究

发布时间：2018-06-18 02:02

本文选题：系统突变 + 经济预测　；参考：《南京航空航天大学》2013年硕士论文

【摘要】：突变现象是系统发展过程中的一种不连续、不平滑现象，这种现象在经济系统里时有发生。突变现象为平稳运行的经济系统带来极大的扰动，对此进行预测、预警意义重大。突变现象发生后，系统运行环境复杂多变，准确把握系统运行趋势很有必要。本文基于传统突变理论、多元统计分析理论、灰数代数理论、贝叶斯推理技术和灰色预测理论，重点研究了经济系统中突变预警建模问题以及突变发生后的经济发展趋势预测问题。论文的主要创新点如下：（1）建立了经济灰色突变预警组合模型，该模型直观、动态、定量的预警经济系统的突变行为。论文给出了利用突变理论解决经济突变问题的统一建模框架和流程，架设了一条社会科学和突变理论之间的桥梁，克服了突变理论难以在经济问题应用的难题，，进一步验证了突变理论解决社会科学问题的可行性。（2）构建了经济突变发生后的灰色泛函预测GFAM(1,1)模型。针对系统发生突变或变革的当期或短期内，由于预测所需要的基本样本数据量无法满足要求，许多经典预测模型失灵问题，本节将泛函理论与灰数代数理论相结合，并运用区间灰数的代数表征技术和Bayes网络推理技术，建立了基于系统突变分析的灰色泛函预测GFAM(1,1)（Gray Function Analysis Model(1,1)）模型，模型充分挖掘和利用系统突变当前时段或突变后较短时间内的信息，以克服传统模型必须在获得足够统计数据后才能进行预测的滞后性缺陷，在系统突发环境下实现科学的推理与预测。之后论证了模型最小二乘估计参数列定理和预测值定理，给出了利用GFAM(1,1)模型预测的步骤。（3）利用突变预警模型系统分析了我国房地产市场突变预警、预测问题。旨在通过系统分析我国的房地产行业现有历史数据，结合主成分分析、多元数据拟合等多元统计分析技术和突变理论，建立一个房地产行业的突变预警系统模型。模型直观、动态、系统的反映房地产业历史数据及当前趋势，实时预警房地产可能发生的系统性突变，为政府针对房地产业的宏观经济调控提供政策性建议，为维护我国房地产业的平稳、健康发展提供理论支持。
[Abstract]:Sudden change is a discontinuous and uneven phenomenon in the process of system development, which occurs from time to time in the economic system. The sudden change brings great disturbance to the smooth running economic system, and it is of great significance to predict it. After the sudden change, the operating environment of the system is complex and changeable, so it is necessary to grasp the running trend of the system accurately. This paper is based on the traditional catastrophe theory, multivariate statistical analysis theory, grey number algebra theory, Bayesian reasoning technology and grey prediction theory. This paper focuses on the modeling of catastrophe early warning in economic system and the prediction of economic development trend after the sudden change occurs. The main innovations of this paper are as follows: (1) A combination model of economic grey catastrophe warning is established, which is intuitive, dynamic and quantitative. This paper presents a unified modeling framework and flow chart to solve the problem of economic catastrophe by using catastrophe theory, builds a bridge between social science and catastrophe theory, and overcomes the difficult problem that catastrophe theory is difficult to apply in economic problems. Furthermore, the feasibility of catastrophe theory to solve social science problems is verified. (2) A grey functional prediction model of GFAM1 / 1) is constructed after the occurrence of economic catastrophe. In view of the problem of failure of many classical prediction models, the functional theory and grey algebraic theory are combined in this section because the basic sample data amount needed for forecasting cannot meet the requirements of the current or short period of system mutation or change. Using the algebraic representation of interval grey numbers and Bayesian network reasoning technology, the grey functional prediction model of GFAMU 1 / 1 Analysis model based on system mutation analysis is established. The model fully exploits and utilizes the information of the current period or the short time after the sudden change of the system, in order to overcome the lag defect that the traditional model has to obtain enough statistical data before it can be predicted. Scientific reasoning and prediction are realized in the system burst environment. Then, the parameter sequence theorem and forecast value theorem of model least square estimation are proved, and the steps of model prediction using GFAM-1) model are given. (3) the catastrophe early warning model is used to analyze the problem of sudden change early warning and prediction of real estate market in China. The purpose of this paper is to systematically analyze the existing historical data of the real estate industry in China, and to establish a catastrophe warning system model of the real estate industry by combining the principal component analysis (PCA), the multivariate data fitting and the catastrophe theory. The model is intuitionistic, dynamic, and systematically reflects the historical data and current trend of real estate industry. It can warn the real estate industry of the possible systemic mutation in real estate in real time, and provide policy advice for the government to adjust and control the real estate industry macroeconomy. In order to maintain the stability of China's real estate industry, the healthy development of theoretical support.
【学位授予单位】：南京航空航天大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F224;F299.23

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