Interval type-2 fuzzy neural networks with asymmetric MFs based on the twice optimization algorithm for nonlinear system identification

DOI10.1016/j.ins.2023.01.134OpenAlexW4319075615MaRDI QIDQ6127111

Unnamed Author, Jiapu Liu, Tao Yan Zhao, Jiangtao Cao

Publication date: 10 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.01.134

zbMATH Keywords

recursive least squares (RLS)adaptive moment estimation (Adam)asymmetric membership function (AMF)interval type-2 neural network (IT2FNN)multi-strategy adaptive differential evolution algorithm (MSADE)twice optimization algorithm (TOA)

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) System identification (93B30) Nonlinear systems in control theory (93C10)

Cites Work

• Dynamic system modeling using a recurrent interval-valued fuzzy neural network and its hardware implementation
• Performance enhancement for neural fuzzy systems using asymmetric membership functions
• Practical method for determining the minimum embedding dimension of a scalar time series
• Direct adaptive type-2 fuzzy neural network control for a generic hypersonic flight vehicle
• A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks
• Independent coordinates for strange attractors from mutual information
• Fuzzy sets
• Centroid of a type-2-fuzzy set

This page was built for publication: Interval type-2 fuzzy neural networks with asymmetric MFs based on the twice optimization algorithm for nonlinear system identification