A neural fuzzy system for soft computing

被引：8

作者：

Ciftcioglu, O. ^{[1
]}

Bittermann, M. S. ^{[1
]}

Sariyildiz, I. S. ^{[1
]}

机构：

[1] Delft Univ Technol, Dept Bldg Technol, NL-2628 CR Delft, Netherlands

来源：

NAFIPS 2007 - 2007 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY | 2007年

关键词：

D O I：

10.1109/NAFIPS.2007.383889

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An innovative neural fuzzy system is considered for soft computing in design. A neural tree structure is considered with nodes of neuronal type, where Gaussian function plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In the system, as result of special provisions, the locations of the Gaussian membership functions of non-terminal nodes happen to be unity, so that the system has several desirable features; it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modeling properties and addressing complexity issues at the same time. A demonstrative application of the model is presented from a demonstrative simple architectural design exercise and the favorable performance for similar applications is highlighted.

引用

页码：489 / +

页数：2

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