为了解决实际研究过程中模糊数据设定不准确的问题,采用模糊数学方法。应用模糊度说明了数据变量模糊化的重要性,给出了模糊变量和模糊变量时间序列的定义,并用计量经济学和数据挖掘例子说明变量模糊化的必要性。结果表明:研究中的很多数据确实具有模糊特性,模糊变量时间序列的应用有利于得到更客观的计量模型及进行时间序列挖掘。模糊变量时间序列的提出对计量经济学和数据挖掘有一定的参考价值。
Some data with fuzzy characteristics are often improperly defined or ignored.This paper proposes that the fuzzy variables and fuzzy variable time series are used for solving the problem.The importance of data fuzziness is described by fuzzy degree.Also the definitions of fuzzy variables and fuzzy variable time series are proposed.The results show that some data have fuzzy characteristics and the application of fuzzy variable time series is beneficial to econometrics and data mining.By using fuzzy variable time series the gap between fuzzy mathematics and econometrics and data mining is narrowed and reduced.