Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Evolving rule-based models: a tool for design of flexible adaptive systems
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Genetic Algorithms and Fuzzy Logic Systems: Soft Computing Perspectives
Genetic Algorithms and Fuzzy Logic Systems: Soft Computing Perspectives
Understanding UMTS Radio Network Modelling, Planning and Automated Optimisation: Theory and Practice
Understanding UMTS Radio Network Modelling, Planning and Automated Optimisation: Theory and Practice
An efficient quantum neuro-fuzzy classifier based on fuzzy entropy and compensatory operation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hierarchical cluster-based multispecies particle-swarm optimization for fuzzy-system optimization
IEEE Transactions on Fuzzy Systems
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
An interval type-2 fuzzy-neural network with support-vector regression for noisy regression problems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Evolutionary Computation
Identification of nonlinear dynamic systems using functional linkartificial neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Dynamical optimal training for interval type-2 fuzzy neural network (T2FNN)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Self-organizing neuro-fuzzy system for control of unknown plants
IEEE Transactions on Fuzzy Systems
Support vector learning mechanism for fuzzy rule-based modeling: a new approach
IEEE Transactions on Fuzzy Systems
Computing derivatives in interval type-2 fuzzy logic systems
IEEE Transactions on Fuzzy Systems
A Functional-Link-Based Neurofuzzy Network for Nonlinear System Control
IEEE Transactions on Fuzzy Systems
Subsethood-product fuzzy neural inference system (SuPFuNIS)
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
This study presents an efficient cluster-based tribes optimization algorithm (CTOA) for designing a functional-link-based neurofuzzy inference system (FLNIS) for prediction applications. The proposed CTOA learning algorithm was used to optimize the parameters of the FLNIS model. The proposed CTOA adopts a self-clustering algorithm to divide the swarm into multiple tribes, and uses different displacement strategies to update each particle. The CTOA also uses a tribal adaptation mechanism to generate or remove particles and reconstruct tribal links. The tribal adaptation mechanism can improve the quality of the tribe and the tribe adaptation. In CTOA, the displacement strategy and the tribal adaptation mechanism depend on the tribal leaders to strengthen the local search ability. Finally, the proposed FLNIS-CTOA method was applied to several prediction problems. The results of this study demonstrate the effectiveness of the proposed CTOA learning algorithm.