DocumentCode :
354220
Title :
Material property prediction using neural-fuzzy network
Author :
Chen, Min-You
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Sheffield Univ., UK
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
1092
Abstract :
A neural-fuzzy network based adaptive fuzzy modelling approach that includes the initial fuzzy model self-generation, significant input selection, partition validation and parameter optimisation was developed for alloy material property prediction. In this approach, the whole procedure of structure identification and parameter optimisation is carried out automatically and efficiently. The proposed adaptive fuzzy modelling approach has been used to construct composition microstructure property fuzzy models for hot rolled alloy steels. Simulation studies demonstrate that the predicted mechanical properties have good agreement with the measured data by using the obtained fuzzy model with only a few rules
Keywords :
adaptive systems; alloy steel; fuzzy neural nets; materials science; optimisation; parameter estimation; steel industry; adaptive fuzzy modelling; alloy steel; fuzzy neural network; identification; material property prediction; parameter optimisation; steel industry; Automatic control; Composite materials; Fuzzy logic; Fuzzy sets; Fuzzy systems; Input variables; Iron alloys; Material properties; Predictive models; Steel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
Type :
conf
DOI :
10.1109/WCICA.2000.863408
Filename :
863408
Link To Document :
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