Hierarchical fuzzy regression tree: A new gradient boosting approach to design a TSK fuzzy model
Z Mei, T Zhao, X Xie - Information Sciences, 2024 - Elsevier
This paper proposes a novel gradient-boosting-based ensemble system with a fuzzy
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …
regression tree (FRT) as its base component for regression tasks. FRT first initializes the rule …
A hybrid systematic review approach on complexity issues in data-driven fuzzy inference systems development
D Kalibatienė, J Miliauskaitė - Informatica, 2021 - content.iospress.com
The data-driven approach is popular to automate learning of fuzzy rules and tuning
membership function parameters in fuzzy inference systems (FIS) development. However …
membership function parameters in fuzzy inference systems (FIS) development. However …
A data-driven fuzzy system for the automatic determination of fuzzy set type based on fuzziness
T Tan, T Zhao - Information Sciences, 2023 - Elsevier
Existing research mainly uses prior knowledge to set all fuzzy sets in a fuzzy system to the
same type. In data-driven fuzzy modeling, automatically determining the type of fuzzy set is …
same type. In data-driven fuzzy modeling, automatically determining the type of fuzzy set is …
Topology structure optimization of evolutionary hierarchical fuzzy systems
T Zhao, Y Zhu, X Xie - Expert Systems with Applications, 2024 - Elsevier
In this paper, a new method of hierarchical fuzzy system modeling for high-dimensional
regression problems is proposed, which is called multi-objective evolutionary hierarchical …
regression problems is proposed, which is called multi-objective evolutionary hierarchical …
One-to-one ensemble mechanism for decomposition-based multi-objective optimization
Multi-objective evolutionary algorithms based on decomposition (MOEA/Ds) have been
generally recognized as competitive techniques for solving multi-objective optimization …
generally recognized as competitive techniques for solving multi-objective optimization …
An interpretable image classification model Combining a fuzzy neural network with a variational autoencoder inspired by the human brain
K Zhang, W Hao, X Yu, T Shao - Information Sciences, 2024 - Elsevier
Fuzzy neural networks (FNNs) have gained attention for their interpretability and self-
learning ability. However, they struggle with interpreting high-dimensional unstructured data …
learning ability. However, they struggle with interpreting high-dimensional unstructured data …
Disjunctive fuzzy neural networks: A new splitting-based approach to designing a T–S fuzzy model
N Wang, W Pedrycz, W Yao, X Chen… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article proposes a new network approach toward the implementation of Takagi–Sugeno
(T–S) fuzzy models referred to as disjunctive fuzzy neural networks (DJFNNs). The proposed …
(T–S) fuzzy models referred to as disjunctive fuzzy neural networks (DJFNNs). The proposed …
A hybrid fuzzy feature selection algorithm for high-dimensional regression problems: An mRMR-based framework
F Aghaeipoor, MM Javidi - Expert Systems with Applications, 2020 - Elsevier
One of the most important factors affecting the interpretability of Fuzzy Rule-Based Systems
(FRBSs) is the number of features used Indeed, the employment of a large number of …
(FRBSs) is the number of features used Indeed, the employment of a large number of …
Interpretable fuzzy logic control for multirobot coordination in a cluttered environment
Mobile robot navigation is an essential problem in robotics. We propose a method for
constructing and training fuzzy logic controllers (FLCs) to coordinate a robotic team …
constructing and training fuzzy logic controllers (FLCs) to coordinate a robotic team …
Design of Hierarchical Neural Networks Using Deep LSTM and Self-organizing Dynamical Fuzzy-Neural Network Architecture
Time series forecasting is an essential and challenging task, especially for large-scale time-
series (LSTS) forecasting, which plays a crucial role in many real-world applications. Due to …
series (LSTS) forecasting, which plays a crucial role in many real-world applications. Due to …