Using Cartesian genetic programming to implement function modelling

被引：0

作者：

Yu Z. ^{[1
]}

Zeng S. ^{[1
]}

Guo Y. ^{[1
]}

Song L. ^{[2
]}

机构：

[1] School of Computer Science, China University of Geosciences, Wu Han

[2] Microelectronics Technology Institute of Beijing

来源：

International Journal of Innovative Computing and Applications | 2011年 / 3卷 / 04期

关键词：

Cartesian genetic programming; CGP; Evolutionary algorithm; Function modelling;

D O I：

10.1504/IJICA.2011.044530

中图分类号：

学科分类号：

摘要：

This paper presents a new method which uses Cartesian genetic programming (CGP) in order to implement function modelling. Since Julian F. Miller proposed the method of CGP, the research and development of CGP mainly trends in the design of the circuit application in recent years; very few scholars have the related research of function modelling in this field. Therefore, the most important feature in this paper is that we apply CGP which is originally used for circuit design to implement function modelling. By numerical test experiments and comparison, we find that this method of function modelling is novel and has the comparative advantages and it is intelligent (self-adaptive, self-organising, self-learning, self-healing, etc.) while it can greatly increase the system speed. © 2011 Inderscience Enterprises Ltd.

引用

页码：213 / 222

页数：9

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