Using a Genetic Algorithm to Derive a Linguistic Summary of Trends in Numerical Time Series

J. Kacprzyk, A. Wilbik, S. Zadrozny
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引用次数: 11

Abstract

The purpose of this paper is to propose a new easily implementable approach to a linguistic summarization of trends that may occur in temporal data, to be more specific - time series. To characterize the trends in time series, we use three parameters: dynamics of change, duration and variability, and apply to them the fuzzy linguistic summaries of data (databases) in the sense of Yager (cf. Yager (1982), Kacprzyk and Yager (2001) and Kacprzyk et al. (2000)) which in the form of natural language-like sentences subsume the very essence of a set of data. A genetic algorithm is used to generate the linguistic summaries sought
用遗传算法推导数值时间序列趋势的语言摘要
本文的目的是提出一种新的易于实现的方法来对可能出现在时间数据中的趋势进行语言总结,更具体地说,是时间序列。为了描述时间序列的趋势,我们使用了三个参数:变化的动态、持续时间和可变性,并将Yager(参见Yager(1982)、Kacprzyk和Yager(2001)以及Kacprzyk等人(2000))意义上的数据(数据库)的模糊语言摘要应用于它们,这些摘要以自然语言的形式包含了一组数据的本质。采用遗传算法生成语言摘要
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