数据挖掘方法在传统预测模型中的应用

数学建模领域中,对于解决不同类型的预测问题有一些经典的预测模型。最近日益流行的数据挖掘技术也有一些针对解决预测问题的独特的数学模型和建模方法。在此对使用传统解析式模型的预测方法与应用数据挖掘技术的数据库模型的预测方法进行了对比,重点分析了2种方法在影响因素的确定、数据规律的寻找方法以及模型侧重点选择上的不同之处,并简单讨论了如何结合2种模型的优点,将数据挖掘技术应用于传统解析式模型的建模过程之中,对已有的解析式预测模型进行改进,进而得出更加可靠准确的预测结果。

Application of data mining methods to traditional prediction mathematical models

Many mathematical models have been developed to solve the forecasting problems.The most commonly used mathematical models are the traditional prediction models.Predictive mode is also one of the two basic modes in data mining methods.Using the database models,there are many particular mathematical models in data mining methods to deal with the forecasting problem.This article made a comparison of the two kinds of prediction models in the methods of finding the influencing factors,analyzing the rule of the data and the emphasis of choosing the decision variables;and then briefly discussed how to apply the data mining methods to the traditional prediction models to combine the advantages of the two to make the prediction more accurate and reliable.