Neuro-Fuzzy Model of Complex Objects Approximation with Discrete Output

被引：0
|
作者：
Katasev, A. S. [1 ]
Kataseva, D., V [1 ]
Emaletdinova, L. Yu [2 ]
机构：
[1] Kazan Natl Res Tech Univ, Informat Secur Syst Dept, Kazan 420111, Russia
[2] Kazan Natl Res Tech Univ, Appl Math & Informat Dept, Kazan 420111, Russia
来源：
2016 2ND INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING, APPLICATIONS AND MANUFACTURING (ICIEAM) | 2016年
关键词：
modeling; approximation; complex object; fuzzy-production rule; neuro-fuzzy model; knowledge base; NETWORKS;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper solves the task of complex objects approximation with a discrete output based on information approach to modeling. We propose a model of fuzzy rules and the inference algorithm on the rules, and describe the neuro-fuzzy model for generation of a knowledge base. The approximation of known data sets and comparison of the results with those of other authors is performed. Examples of knowledge bases generation of the expert diagnostic systems in medicine, oil industry and information security show effectiveness of the proposed approach.
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页数：5
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