Parse-matrix evolution for symbolic regression

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	Parse-matrix evolution for symbolic regression
	Luo ZT(罗长童); Zhang SL(张绍良)
刊名	ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
	2012-09-01
通讯作者邮箱	luo@imech.ac.cn;zhang@na.cse.nagoya-u.ac.jp
卷号	25 期号:6 页码:1182-1193
关键词	Genetic programming Data analysis Symbolic regression Grammatical evolution Artificial intelligence Evolutionary computation Nonlinear-Systems Identification
ISSN号	0952-1976
通讯作者	Luo, CT ; Chinese Acad Sci, Inst Mech, Beijing 100190, Peoples R China.
产权排序	[Luo, Changtong] Chinese Acad Sci, Inst Mech, Beijing 100190, Peoples R China;[Zhang, Shao-Liang] Nagoya Univ, Dept Computat Sci & Engn, Nagoya, Aichi 4648603, Japan
合作状况	国际
中文摘要	Data-driven model is highly desirable for industrial data analysis in case the experimental model structure is unknown or wrong, or the concerned system has changed. Symbolic regression is a useful method to construct the data-driven model (regression equation). Existing algorithms for symbolic regression such as genetic programming and grammatical evolution are difficult to use due to their special target programming language (i.e., LISP) or additional function parsing process. In this paper, a new evolutionary algorithm, parse-matrix evolution (PME), for symbolic regression is proposed. A chromosome in PME is a parse-matrix with integer entries. The mapping process from the chromosome to the regression equation is based on a mapping table. PME can easily be implemented in any programming language and free to control. Furthermore, it does not need any additional function parsing process. Numerical results show that PME can solve the symbolic regression problems effectively.
学科主题	空气动力学
分类号	一类
收录类别	SCI ; EI
资助信息	This work was partially supported by the National Natural Science Foundation of China (Grant No. 90916028).
原文出处	http://dx.doi.org/10.1016/j.engappai.2012.05.015
语种	英语
WOS记录号	WOS:000308122700008
公开日期	2013-01-18
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/46613]
专题	力学研究所_高温气体动力学国家重点实验室
推荐引用方式 GB/T 7714	Luo ZT,Zhang SL. Parse-matrix evolution for symbolic regression[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2012,25(6):1182-1193.
APA	罗长童,&张绍良.(2012).Parse-matrix evolution for symbolic regression.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,25(6),1182-1193.
MLA	罗长童,et al."Parse-matrix evolution for symbolic regression".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 25.6(2012):1182-1193.