Parametric Fuzzy Model Identification Based on a Hybrid Ant Colony Algorithm

被引：0
|
作者：
Khodashinsky, I. A. [1 ]
Dudin, P. A. [1 ]
机构：
[1] Tomsk Univ Control Syst & Radio Elect, Tomsk, Russia
来源：
OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING | 2008年 / 44卷 / 05期
基金：
俄罗斯基础研究基金会;
关键词：
D O I：
10.3103/S8756699008050038
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
Applying the ant colony algorithm for solving the problem of parametric fuzzy model identification is presented. Transition from continuous optimization to discrete one via constructing a complete oriented decision-search graph is determined. A gradient algorithm is considered as the second optimization step. Experiments for analyzing the performance of the algorithms for optimization and fuzzy system are described.
引用
收藏
页码：402 / 411
页数：10
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