4.7 Article

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

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

A new QoS prediction model using hybrid IOWA-ANFIS with fuzzy C-means, subtractive clustering and grid partitioning

Walayat Hussain et al.

Summary: The study proposes a novel fuzzy time series prediction model, the CI-ANFIS model, which reduces data dimension, handles the nonlinear relationship of cloud QoS dataset, and outperforms all current techniques in terms of prediction accuracy.

INFORMATION SCIENCES (2022)

Article Computer Science, Information Systems

Sensitivity analysis of Takagi-Sugeno fuzzy neural network

Jian Wang et al.

Summary: This paper defines a measure of statistical sensitivity of a zero-order Takagi-Sugeno (TS) fuzzy neural network (FNN) with respect to perturbation of weights and parameters, as well as derive measures of sensitivity of the system to additive and multiplicative noises to the consequent parameters. These sensitivity measures are used as regularizers to the loss function during training, and their effectiveness is demonstrated through simulation results on classification and regression problems.

INFORMATION SCIENCES (2022)

Article Computer Science, Information Systems

Design of stabilized polynomial-based ensemble fuzzy neural networks based on heterogeneous neurons and synergy of multiple techniques

Congcong Zhang et al.

Summary: In this study, a novel category of polynomial-based ensemble fuzzy neural networks (PEFNNs) are proposed to improve the performance of the model when dealing with nonlinear regression problems. The hybrid network structure composed of heterogeneous neurons and multiple techniques synergistically used to reinforce the performance of PEFNNs are key highlights. Multiple approaches, including an enhanced topology based on fuzzy module and enhanced interconnection (FM&EI) and evolutionary algorithms, are considered to construct the ensemble model.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

FCM-RDpA: TSK fuzzy regression model construction using fuzzy C-means clustering, regularization, Droprule, and Powerball Adabelief

Zhenhua Shi et al.

Summary: This paper proposes the FCM-RDpA algorithm, which enhances Takagi-Sugeno-Kang fuzzy systems optimization for regression problems by improving MBGD-RDA and integrating Powerball AdaBelief, showing superiority especially in higher feature dimensionalities.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

An interpretable Neural Fuzzy Hammerstein-Wiener network for stock price prediction

Chen Xie et al.

Summary: This paper proposes an interpretable regression model for stock price prediction, which integrates a neuro-fuzzy system with the Hammerstein Wiener model. Experimental results show that the proposed Neural Fuzzy Hammerstein-Wiener (NFHW) outperforms other neuro-fuzzy systems and the conventional Hammerstein-Wiener model in stock price prediction.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

Design of fuzzy system-fuzzy neural network-backstepping control for complex robot system

Kunming Zheng et al.

Summary: This study addresses the control problem of complex robot systems with uncertainties and disturbances using the FS-FNN-BSC system, which guarantees accurate, stable and efficient control. By utilizing fuzzy system and fuzzy neural network technologies, modeling and non-modeling information is approximated and predicted, respectively. The stability of the FS-FNN-BSC system is proved based on the Lyapunov stability theorem, and its superiority is demonstrated through quantitative comparison with existing intelligent control methods on the series and parallel robots.

INFORMATION SCIENCES (2021)

Article Computer Science, Information Systems

Accelerated learning algorithms of general fuzzy min-max neural network using a novel hyperbox selection rule

Thanh Tung Khuat et al.

Summary: This paper proposes a method to accelerate the training process of general fuzzy min-max neural network by removing hyperboxes that do not satisfy expansion or aggregation conditions, thus reducing training time. Experimental results show a significant decrease in training time for both online and agglomerative learning algorithms using the proposed method.

INFORMATION SCIENCES (2021)

Article Automation & Control Systems

Adaptive Type-2 FNN-Based Dynamic Sliding Mode Control of DC-DC Boost Converters

Jiahui Wang et al.

Summary: This paper introduces a dynamic sliding mode control approach for robust voltage regulation of dc-dc boost converters using interval type-2 fuzzy neural networks. The proposed method includes design of sliding surface, dynamic SMC law, and IT2FNN-based SMC law to handle uncertainties and improve tracking error system stability. Online learning algorithms and gradient descent method are used to update IT2FNN for better uncertainty management. Simulation results support the effectiveness of the proposed adaptive IT2FNN-based dynamic SMC method.

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Toward a development of general type-2 fuzzy classifiers applied in diagnosis problems through embedded type-1 fuzzy classifiers

Emanuel Ontiveros-Robles et al.

SOFT COMPUTING (2020)

Article Computer Science, Artificial Intelligence

Optimize TSK Fuzzy Systems for Regression Problems: Minibatch Gradient Descent With Regularization, DropRule, and AdaBound (MBGD-RDA)

Dongrui Wu et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

Conjugate gradient-based Takagi-Sugeno fuzzy neural network parameter identification and its convergence analysis

Tao Gao et al.

NEUROCOMPUTING (2019)

Article Automation & Control Systems

High order α-planes integration: A new approach to computational cost reduction of General Type-2 Fuzzy Systems

Emanuel Ontiveros et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2018)

Article Computer Science, Artificial Intelligence

IC-FNN: A Novel Fuzzy Neural Network With Interpretable, Intuitive, and Correlated-Contours Fuzzy Rules for Function Approximation

Mohammad Mehdi Ebadzadeh et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2018)

Article Computer Science, Information Systems

A Polak-Ribiere-Polyak Conjugate Gradient-Based Neuro-Fuzzy Network and Its Convergence

Tao Gao et al.

IEEE ACCESS (2018)

Article Computer Science, Artificial Intelligence

Fuzzy (c plus p)-Means Clustering and Its Application to a Fuzzy Rule-Based Classifier: Toward Good Generalization and Good Interpretability

Jacek M. Leski

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

CFNN: Correlated fuzzy neural network

Mohammad Mehdi Ebadzadeh et al.

NEUROCOMPUTING (2015)

Article Computer Science, Artificial Intelligence

Simplified Interval Type-2 Fuzzy Neural Networks

Yang-Yin Lin et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2014)

Proceedings Paper Computer Science, Artificial Intelligence

A Recursive SVD-based Least Squares Algorithm With Forgetting Factors for Neuro-Fuzzy Modeling

Chen-Sen Ouyang et al.

2013 14TH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD 2013) (2013)

Article Computer Science, Artificial Intelligence

Convergence analysis of online gradient method for BP neural networks

Wei Wu et al.

NEURAL NETWORKS (2011)

Article Computer Science, Information Systems

A modified gradient-based neuro-fuzzy learning algorithm and its convergence

Wei Wu et al.

INFORMATION SCIENCES (2010)

Article Computer Science, Artificial Intelligence

Enhanced Karnik-Mendel Algorithms

Dongrui Wu et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2009)

Article Computer Science, Information Systems

A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks

Juan R. Castro et al.

INFORMATION SCIENCES (2009)

Article Computer Science, Artificial Intelligence

Nonstationary Fuzzy Sets

Jonathan M. Garibaldi et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2008)

Article Automation & Control Systems

Simultaneous Structure Identification and Fuzzy Rule Generation for Takagi-Sugeno Models

Nikhil R. Pal et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2008)

Article Automation & Control Systems

Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)

CH Wang et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2004)