Abstract
In this paper two bio-inspired methods are used to optimize the type-2 fuzzy inference system integrator in an ensemble of three neural networks with type-2 fuzzy weights. The genetic algorithm and particle swarm optimization are used to optimize the type-2 fuzzy system integrators that work in response integration of the ensemble neural network for obtaining the final output. In this work an optimized type-2 fuzzy inference system integrator to perform the integration for an ensemble of three neural networks and the results for the two bio-inspired methods are presented. The proposed approach is applied to a case of time series prediction, specifically for the Mackey-Glass time series
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
