Abstract
An integrated fuzzy and grey model and its applications to the prediction control problems are presented. The basic grey model GM(1,1) is accompanied with the adaptive fuzzy method to improve its prediction capability. The gradient descent scheme is applied to the fuzzy rules to determine whether the predicted results from the grey model should be adjusted. The quantity of adjustment is judged from the degrees of the correlation between the past data and the current input. We select a few most correlated patterns to decide the direction of adjustment. Due to the simplicity of the structure and its fast learning characteristics, this model is good as a real-time controller. Under the proposed methodology, the simulation results are shown to be superior to those systems which exploit complicated control variables and rules. A well-known difference equation and the weather forecast prediction problems are depicted to verify the superiority of the proposed method.
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.
