id: 05802500
dt: j
an: 05802500
au: Gao, X.Z.; Ovaska, S.J.; Wang, X.
ti: A simplified linguistic information feedback-based dynamical fuzzy system.
so: Neural Comput. Appl. 19, No. 7, 1029-1041 (2010).
py: 2010
pu: Springer-Verlag, London
la: EN
cc: 
ut: fuzzy systems; linguistic information; feedback systems; dynamics; time
    series; prediction
ci: 
li: doi:10.1007/s00521-010-0354-z
ab: Summary: Inspired by the linguistic information feedback-based dynamical
    fuzzy system (LIFDFS) recently proposed by the authors, we present a
    simplified LIFDFS (S-LIFDFS) model in this paper, which has a simpler
    linguistic information feedback structure. Compared with the LIFDFS,
    the S-LIFDFS can offer us with a considerably reduced computational
    complexity. We first give a detailed description of its underlying
    principle. Based on the gradient descent method, an adaptive learning
    algorithm for the feedback parameters is next derived. We also discuss
    the application of this S-LIFDFS in time series prediction. Three
    evaluation examples including prediction of two artificial time
    sequences and the well-known Box-Jenkins gas furnace data are
    demonstrated here. Simulation results illustrate that with a compact
    structure, our S-LIFDFS can still retain the advantage of inherent
    dynamics of linguistic information feedback and is, therefore, well
    suited for handling temporal problems like prediction, modeling, and
    control.
rv: