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Designing expert system for in situ toughened Si3N4 based on adaptive neural fuzzy inference system and genetic algorithms

Zeng, Q.F. and Zhang, L.T. and Xu, Y.D. and Cheng, L.F. and Yan, X.T. and Zu, J.K. and Dai, G.Z. (2009) Designing expert system for in situ toughened Si3N4 based on adaptive neural fuzzy inference system and genetic algorithms. Materials and Design, 30 (2). pp. 256-259. ISSN 0264-1275

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Abstract

Adaptive neural fuzzy inference system (ANFIS) combined with GAs is applied to develop an expert system for designing in situ toughened Si3N4 in this paper. ANFIS combines fuzzy linguistic descriptions with accurate experimental data. GAs have been successfully applied in searching and optimizing very large and varied data spaces. ANFIS models were developed in this paper to predict mechanical properties based on sintering processing or microstructure. And GAs models are developed to predict sintering processing based on mechanical properties or microstructure of this material. A software package was developed to realize the applications mentioned above easily and quickly.

Item type: Article
ID code: 19351
Keywords: engineering ceramics, selection for material properties, selection of material processes, Manufactures, Engineering design, Mechanics of Materials, Materials Science(all), Mechanical Engineering
Subjects: Technology > Manufactures
Technology > Engineering (General). Civil engineering (General) > Engineering design
Department: Faculty of Engineering > Design, Manufacture and Engineering Management
Related URLs:
    Depositing user: Strathprints Administrator
    Date Deposited: 02 Jun 2010 10:23
    Last modified: 05 Sep 2014 03:16
    URI: http://strathprints.strath.ac.uk/id/eprint/19351

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