By Topic

A neuro fuzzy logic approach to material processing

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
$33 $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)
L. Arafeh ; Coll. of Eng. & Technol., Coll. of Eng. & Technol., Hebron, Israel ; H. Singh ; S. K. Putatunda

A new application of fuzzy systems to the processing of materials is presented. The relationships between temperature, time, and the impact strength of an austempered ductile iron (ADI) part are adaptively modeled. Four fuzzy and neuro fuzzy approaches have been used to build predictive models. These are: a fuzzy based model, a backpropagation based neuro fuzzy model, a clustering based model, and a clustering backpropagation based neuro fuzzy model. The clustering approach, using the subclustering method, yielded the best predictive results when all models had been given the same input-output training data. The backpropagation based neuro fuzzy approach suffers from the lack of a higher number of input-output data training sets. All preliminary results obtained suggest the adequacy of the fuzzy based and neuro fuzzy based modeling techniques to tackle those types of problems in the material processing areas

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)  (Volume:29 ,  Issue: 3 )