文章基本信息

标题：Fuzzy Supervised Multi-Period Time Series Forecasting
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作者：Galina Ilieva
期刊名称：Cybernetics and Information Technologies
印刷版ISSN：1311-9702
电子版ISSN：1314-4081
出版年度：2019
卷号：19
期号：2
页码：74-86
DOI：10.2478/cait-2019-0016
出版社：Bulgarian Academy of Science
摘要：The goal of this paper is to propose a new method for fuzzy forecasting of time series with supervised learning and k-order fuzzy relationships. In the training phase based on k previous historical periods, a multidimensional matrix of fuzzy dependencies is constructed. During the test stage, the fitted fuzzy model is run for validating the observations and each output value is predicted by using a fuzzy input vector of k previous intervals. The proposed algorithm is verified by a benchmark dataset for fuzzy time series forecasting. The results obtained are similar or better than those of other fuzzy time series prediction methods. Comparative analysis shows the high potential of the new algorithm as an alternative to fuzzy prediction and reveals some opportunities for its further improvement.
关键词：Fuzzy set; fuzzy time series; forecasting; membership function; fuzzy; relationships