Title :
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
fDate :
7/1/2000 12:00:00 AM
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;
Journal_Title :
Magnetics, IEEE Transactions on
