基于数据挖掘的经济预测模型可行性研究

Rui Min
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引用次数: 2

摘要

经济预测是建立在对人类经济活动运行规律的认知和对未来经济发展状况和趋势的逻辑推断的基础上的。传统的经济模型大多是线性模型,具有一定的经济预测能力,但也存在明显的缺点,如难以反映经济系统中广泛的非线性关系。由于经济系统非常复杂,内部因素众多,且各因素之间具有很强的耦合性、时变性和非线性特征,因此经济系统的建模与预测是一项极具挑战性的研究。在经济环境快速变化的背景下,经济变量与外部随机干扰因素之间的关系将更有可能发生变化,而不是保持一定的关系。经济运行形势的复杂多变,给经济发展带来了更多的不确定性。因此,一些经典的经济模型已经不能满足中国实证研究的需要。我们迫切需要从动态不确定性的视角对中国经济问题进行实证研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feasibility Study of Economic Forecasting Model based on Data Mining
Economic forecast is based on the cognition of the operation law of human economic activities and the logical inference of the future economic development situation and trend. Most of the traditional economic models are linear models, which have certain economic forecasting ability, but also have obvious shortcomings, such as it is difficult to reflect the extensive nonlinear relationship in the economic system. Because the economic system is very complex, there are many internal factors, and there are strong coupling, time-varying and nonlinear characteristics among them, so the modeling and forecasting of economic system is a very challenging research. In the context of rapid changes in the economic environment, the relationship between economic variables and external random disturbance factors will be more likely to change rather than maintain a certain relationship. The complex and changeable situation of economic operation leads to more uncertainties in economic development. Therefore, some classical economic models can not meet the needs of empirical research in China. We urgently need to conduct empirical research on China's economic problems from the perspective of dynamic uncertainty.
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