Abstract
For the problems occurring in a least square method model, a fuzzy model, and a neural network model for flatness pattern recognition, a fuzzy neural network model for flatness pattern recognition with only three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern, based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm. The model not only had definite physical meanings in its inner nodes, but also had strong self-adaptability, anti-interference ability, high recognition precision, and high velocity, thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient, practical, and novel method for flatness pattern recognition.
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.
