Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

摘要: We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on MSSA information granulation (IG). The is optimization whose method associated with analysis solution space. mechanism realized using non-dominated sorting-based strategy. In system, exploited to carry out parametric model achieve its structural optimization. attained C-Means clustering algorithm. overall comes in form two mechanisms: structure (such as number input variables be used, specific subset variables, membership functions, polynomial type) parameter (viz. apexes function). developed by C-Means, whereas via least squares method. evaluation performance proposed was conducted three representative numerical examples such gas furnace, NOx emission process data, Mackey-Glass time series. also compared quality some "conventional" models encountered literature.