Title :
Multi-dimensional fuzzy interpolation neural network
Author :
Li, Dayou ; Yue, Yong ; Maple, Carsten ; Schetinin, Vitaly ; Qiu, Hua
Author_Institution :
Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
Abstract :
This paper presents a multi-dimensional fuzzy interpolation neural network (FINN) which extends fuzzy interpolation that was developed to approximate single input single output functions to multi-dimensional space. The multidimensional fuzzy interpolation piecewise approximates multiple-input-single-output functions with small hyper-surfaces defined over fuzzy regions. The vertices of these fuzzy regions are represented by weighted multivariate fuzzy sets which are defined over the input space of a function. Optimally arranging the fuzzy sets in the input space can achieve arbitrary accurate approximations. The proposed FINN is able to establish the optimisation of the fuzzy sets. It was used to approximate the energy distribution of light for light chip and optical fibre alignment.
Keywords :
fuzzy neural nets; fuzzy set theory; interpolation; energy distribution; fuzzy set theory; light chip; multidimensional fuzzy interpolation neural network; optical fibre alignment; single input single output function approximation; Automation; Bismuth; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Input variables; Interpolation; Multidimensional systems; Neural networks; Space technology; fuzzy systems; interpolation; modeling;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262941