Numerical Prediction of Time Series Based on FCMs with Information Granules
Keywords:
Fuzzy Cognitive Maps (FCMs), time series, prediction, , information granulesAbstract
The prediction of time series has been widely applied to many fields such
as enrollments, stocks, weather and so on. In this paper, a new prediction method
based on fuzzy cognitive map with information granules is proposed, in which fuzzy cmeans
clustering algorithm is used to automatically abstract information granules and
transform the original time series into granular time series, and subsequently fuzzy
cognitive map is used to describe these granular time series and perform prediction.
two benchmark time series are used to validate feasibility and effectiveness of proposed
method. The experimental results show that the proposed prediction method can
reach better prediction accuracy. Additionally, the proposed method is also able to
precess the modeling and prediction of large-scale time series.
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