A machine learning approach for the support of preliminary structural design

被引：12
|
作者：
Freischlad, M [1 ]
Schnellenbach-Held, M [1 ]
机构：
[1] Univ Duisburg Essen, Inst Concrete Struct, Dept Civil Engn, D-45144 Essen, Germany
来源：
ADVANCED ENGINEERING INFORMATICS | 2005年 / 19卷 / 04期
关键词：
knowledge acquisition; linguistic fuzzy modeling; genetic fuzzy systems;
D O I：
10.1016/j.aei.2005.07.001
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with the representation and acquisition of structural design knowledge using fuzzy systems. A new approach for linguistic fuzzy modeling as well as a multi-objective evolutionary algorithm for the data-driven design of fuzzy systems is presented. The developed genetic fuzzy system has been applied to test problems and real-world tasks. Making use of the proposed approaches the interpretability of fuzzy systems can be increased without loss of accuracy. The developed system facilitates the knowledge acquisition and improves the maintainability of the knowledge base. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：281 / 287
页数：7
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