Self-learning type-2 fuzzy systems with adaptive rule reduction for time series forecasting

Self-learning type-2 fuzzy systems with adaptive rule reduction for time series forecasting

In rapidly changing scenarios, uncertainty and chaotic oscillations often obstruct time series prediction. However, Type-1 fuzzy systems face challenges in handling high uncertainty levels, therefore, Type-2 fuzzy systems become a better solution. Nonetheless, the complexity of Type-2 fuzzy models c...

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Bibliographic Details
Main Authors: Abdulwhab Alkharashi, Gaganjot Kaur, Hadeel Alsolai, Hatim Dafaalla, Somia Asklany, Othman Alrusaini, Ali Alqazzaz, Menwa Alshammeri
Format: Article
Language:English
Published: PeerJ Inc. 2025-07-01
Series:PeerJ Computer Science
Subjects:
Fuzzy
Systems
Chaotic
Series
Time
Forcasting
Online Access:https://peerj.com/articles/cs-3004.pdf
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