IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part I
An affine fuzzy model with local and global interpretations
Applied Soft Computing
Information Sciences: an International Journal
Optimization of fuzzy systems using group-based evolutionary algorithm
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
An Evolutionary Functional Link Neural Fuzzy Model for Financial Time Series Forecasting
International Journal of Applied Evolutionary Computation
Adaptive neural complementary sliding-mode control via functional-linked wavelet neural network
Engineering Applications of Artificial Intelligence
International Journal of Intelligent Information and Database Systems
International Journal of Intelligent Information and Database Systems
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This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural network (FLNN) to the consequent part of the fuzzy rules. This study uses orthogonal polynomials and linearly independent functions in a functional expansion of the FLNN. Thus, the consequent part of the proposed FLNFN model is a nonlinear combination of input variables. An online learning algorithm, which consists of structure learning and parameter learning, is also presented. The structure learning depends on the entropy measure to determine the number of fuzzy rules. The parameter learning, based on the gradient descent method, can adjust the shape of the membership function and the corresponding weights of the FLNN. Furthermore, results for the universal approximator and a convergence analysis of the FLNFN model are proven. Finally, the FLNFN model is applied in various simulations. Results of this study demonstrate the effectiveness of the proposed FLNFN model.