By Topic

Hybrid optimization in electromagnetics using sensitivity information from a neuro-fuzzy model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Rashid, K. ; Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK ; Ramirez, J.A. ; Freeman, E.M.

The use of sensitivity information from a neuro-fuzzy model for the purpose of optimization is investigated in this paper. This approach permits the application of classic deterministic or hybrid optimization methods in establishing the global minimum of any approximated objective function using neuro-fuzzy modeling. For nondifferentiable functions this approach is of great benefit. An analytical problem and the TEAM 22 benchmark problem are investigated. Results using the genetic algorithm method and the sequential quadratic programming method in sequence show the usefulness of the formulation

Published in:

Magnetics, IEEE Transactions on  (Volume:36 ,  Issue: 4 )