Using Cartesian genetic programming to implement function modelling. (1st January 2011)

• Record Type: Journal Article
• Authors: Yu, Zhangyi; Zeng, Sanyou; Guo, Yan; Song, Liguo
• Is Part Of: International journal of innovative computing and applications. Volume 3:Number 4(2011)
• Page Start: 213
• Page End: 222
• Publication Date: 2011-01-01
• Subjects: Cartesian genetic programming -- CGP -- evolutionary algorithm -- function modelling; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• DOI: 10.1504/IJICA.2011.044530
• Languages: English
• ISSNs: 1751-648X

Abstract

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.