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首页> 外文期刊>Comparative Economic Research >The Forecasting of Labour Force Participation and the Unemployment Rate in Poland and Turkey Using Fuzzy Time Series Methods
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The Forecasting of Labour Force Participation and the Unemployment Rate in Poland and Turkey Using Fuzzy Time Series Methods

机译：运用模糊时间序列方法预测波兰和土耳其的劳动力参与率和失业率

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摘要

Fuzzy time series methods based on the fuzzy set theory proposed by Zadeh (1965) was first introduced by Song and Chissom (1993). Since fuzzy time series methods do not have the assumptions that traditional time series do and have effective forecasting performance, the interest on fuzzy time series approaches is increasing rapidly. Fuzzy time series methods have been used in almost all areas, such as environmental science, economy and finance. The concepts of labour force participation and unemployment have great importance in terms of both the economy and sociology of countries. For this reason there are many studies on their forecasting. In this study, we aim to forecast the labour force participation and unemployment rate in Poland and Turkey using different fuzzy time series methods.
机译：Song和Chissom（1993）首次引入了基于Zadeh（1965）提出的模糊集理论的模糊时间序列方法。由于模糊时间序列方法没有传统时间序列所具有的假设并且具有有效的预测性能，因此对模糊时间序列方法的兴趣正在迅速增加。模糊时间序列方法已用于几乎所有领域，例如环境科学，经济和金融。就国家的经济和社会学而言，劳动力参与和失业的概念非常重要。因此，对它们的预测有很多研究。在这项研究中，我们旨在使用不同的模糊时间序列方法来预测波兰和土耳其的劳动力参与率和失业率。

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