Abstract
A fuzzy model based on support vector regression (SVR) and particle swarm optimization (PSO) for the property prediction of heat treatment process of alloy steels is presented in this paper. First, a SVR model is built and the parameters of SVR are optimized by using the grid optimization algorithm, a set of equivalent fuzzy IF-THEN rules is generated from the obtained support vectors, then PSO is utilized to obtain a optimal fuzzy model with reduced rule (support vector) which approximate pre images of the original SVR model. The proposed modeling approach has been used for the mechanical property prediction in hot-rolled steels. Preliminary results reveal that the proposed modelling approach can lead to accurate and flexible fuzzy models.
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.
