Recurrent neuro-fuzzy hybrid-learning approach to accurate system modeling
Fuzzy Sets and Systems
An adaptive recurrent fuzzy system for nonlinear identification
Applied Soft Computing
Prediction of laser solid freeform fabrication using neuro-fuzzy method
Applied Soft Computing
Supervised and Reinforcement Evolutionary Learning for Wavelet-based Neuro-fuzzy Networks
Journal of Intelligent and Robotic Systems
Adaptive fuzzy wavelet network control design for nonlinear systems
Fuzzy Sets and Systems
Pattern recognition using neural-fuzzy networks based on improved particle swam optimization
Expert Systems with Applications: An International Journal
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
A recurrent fuzzy filter for the analysis of lung sounds
Fuzzy Sets and Systems
A recurrent self-evolving interval type-2 fuzzy neural network for dynamic system processing
IEEE Transactions on Fuzzy Systems
Multi groups cooperation based symbiotic evolution for TSK-type neuro-fuzzy systems design
Expert Systems with Applications: An International Journal
Efficient reinforcement hybrid evolutionary learning for recurrent wavelet-based neuro-fuzzy systems
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
A locally recurrent fuzzy neural network with support vector regression for dynamic-system modeling
IEEE Transactions on Fuzzy Systems
New model for system behavior prediction based on belief rule based systems
Information Sciences: an International Journal
Recurrent fuzzy system design using elite-guided continuous ant colony optimization
Applied Soft Computing
Expert Systems with Applications: An International Journal
Condition-based maintenance of dynamic systems using online failure prognosis and belief rule base
Expert Systems with Applications: An International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
Hi-index | 0.01 |
This paper presents a wavelet-based recurrent fuzzy neural network (WRFNN) for prediction and identification of nonlinear dynamic systems. The proposed WRFNN model combines the traditional Takagi-Sugeno-Kang (TSK) fuzzy model and the wavelet neural networks (WNN). This paper adopts the nonorthogonal and compactly supported functions as wavelet neural network bases. Temporal relations embedded in the network are caused by adding some feedback connections representing the memory units into the second layer of the feedforward wavelet-based fuzzy neural networks (WFNN). An online learning algorithm, which consists of structure learning and parameter learning, is also presented. The structure learning depends on the degree measure to obtain the number of fuzzy rules and wavelet functions. Meanwhile, the parameter learning is based on the gradient descent method for adjusting the shape of the membership function and the connection weights of WNN. Finally, computer simulations have demonstrated that the proposed WRFNN model requires fewer adjustable parameters and obtains a smaller RMS error than other methods.