Interval type-2 fuzzy neural networks for chaotic time series prediction: A concise overview

M Han, K Zhong, T Qiu, B Han - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Chaotic time series widely exists in nature and society (eg, meteorology, physics,
economics, etc.), which usually exhibits seemingly unpredictable features due to its inherent …

Big data analytics and application for logistics and supply chain management

K Govindan, TCE Cheng, N Mishra, N Shukla - … Research Part E: Logistics …, 2018 - Elsevier
This special issue explores big data analytics and applications for logistics and supply chain
management by examining novel methods, practices, and opportunities. The articles present …

A modified interval type-2 Takagi-Sugeno fuzzy neural network and its convergence analysis

T Gao, X Bai, C Wang, L Zhang, J Zheng, J Wang - Pattern Recognition, 2022 - Elsevier
In this paper, to compute the firing strength values of type-2 fuzzy models, a soft version of
minimum is presented, which endows the fuzzy model with the ability to solve large …

Nonstationary fuzzy neural network based on FCMnet clustering and a modified CG method with Armijo-type rule

B Zhang, X Gong, J Wang, F Tang, K Zhang, W Wu - Information Sciences, 2022 - Elsevier
Nonstationary fuzzy inference systems (NFISs) model the variation in opinions of individual
experts and expert groups. They have the capability similar to type-2 fuzzy systems in some …

An incremental learning of concept drifts using evolving type-2 recurrent fuzzy neural networks

M Pratama, J Lu, E Lughofer… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
The age of online data stream and dynamic environments results in the increasing demand
of advanced machine learning techniques to deal with concept drifts in large data streams …

Optimal design of adaptive type-2 neuro-fuzzy systems: A review

S Hassan, MA Khanesar, E Kayacan, J Jaafar… - Applied Soft …, 2016 - Elsevier
Type-2 fuzzy logic systems have extensively been applied to various engineering problems,
eg identification, prediction, control, pattern recognition, etc. in the past two decades, and the …

Refined fault tolerant tracking control of fixed-wing UAVs via fractional calculus and interval type-2 fuzzy neural network under event-triggered communication

Z Yu, Z Yang, P Sun, Y Zhang, B Jiang, CY Su - Information Sciences, 2023 - Elsevier
The refined fault tolerant tracking control (FTTC) scheme is developed for multiple fixed-wing
unmanned aerial vehicles (UAVs) against actuator faults and wind effects under event …

A data-knowledge-driven interval type-2 fuzzy neural network with interpretability and self-adaptive structure

K Bai, W Zhang, S Wen, C Zhao, W Meng, Y Zeng… - Information …, 2024 - Elsevier
Interval type-2 fuzzy neural networks (IT2FNNs) have gained sustainable attention and wide
applications because of their power of adaptive fuzzy modeling. Although the existing …

Self-evolving function-link interval type-2 fuzzy neural network for nonlinear system identification and control

CM Lin, TL Le, TT Huynh - Neurocomputing, 2018 - Elsevier
Determining a network size for a fuzzy neural network structure is very important, and it is
often difficult to obtain the most suitable value. This study develops a self-evolving function …

Deep stacked stochastic configuration networks for lifelong learning of non-stationary data streams

M Pratama, D Wang - Information Sciences, 2019 - Elsevier
The concept of SCN offers a fast framework with universal approximation guarantee for
lifelong learning of non-stationary data streams. Its adaptive scope selection property …