A general approach for extracting sensitivity analysis from a neuro-fuzzy model

Author

Rashid, Kashif ; Ramirez, Jaime A. ; Freeman, Ernest M.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK

Volume

36

Issue

4

fYear

2000

fDate

7/1/2000 12:00:00 AM

Firstpage

1066

Lastpage

1070

Abstract

The problem of obtaining sensitivity analysis information from an even M-input N-membership function neuro-fuzzy model is addressed in this paper. Subsequently, this permits the application of classic deterministic optimization methods in order to find the global optimum of any objective function approximated using neuro-fuzzy modeling. For nondifferentiable functions this approach is of great benefit. Results from a practical electromagnetic optimization problem are presented

Keywords

deterministic algorithms; electrical engineering computing; electromagnetic field theory; fuzzy neural nets; minimisation; sensitivity analysis; classic deterministic optimization methods; electromagnetic optimization problem; even M-input N-membership function neuro-fuzzy model; global optimum; neuro-fuzzy model; nondifferentiable functions; objective function; sensitivity analysis; Computational intelligence; Data mining; Electromagnetic analysis; Fuzzy neural networks; Fuzzy sets; Information analysis; Input variables; Intelligent networks; Optimization methods; Sensitivity analysis;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/20.877625

Filename

877625