Time Series Prediction Using Sparse Autoencoder and High-Order Fuzzy Cognitive Maps

The problem of time series prediction based on fuzzy cognitive maps (FCMs) is unresolved. Although many methods have been proposed to cope with this issue, the performance of these methods is far from satisfactory. Traditional FCM-based predictors have three limitations. First, current feature extra...

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Bibliographic Details
Published in:	IEEE transactions on fuzzy systems Vol. 28; no. 12; pp. 3110 - 3121
Main Authors:	Wu, Kai, Liu, Jing, Liu, Penghui, Yang, Shanchao
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.12.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Cognitive maps Cognitive models Computational modeling Feature extraction Fuzzy cognitive maps Fuzzy cognitive maps (FCMs) fuzzy time series Machine learning Numerical models Prediction algorithms Prediction models Predictive models sparse autoencoder (SAE) Time series Time series analysis time series prediction
ISSN:	1063-6706, 1941-0034
Online Access:	Get full text
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