期刊导航

论文摘要

LDecode:具有线性复杂度的GEP适应度评价算法

LDecode:A Novel Decoding Algorithm on Gene Expression Programmingwith Linear Complexity

作者:陈瑜(四川大学 计算机学院,四川 成都 6100642);唐常杰(四川大学 计算机学院,四川 成都 6100642);李川(四川大学 计算机学院,四川 成都 6100642)

Author:(School of Computer Sci., Sichuan Univ., Chengdu 610064, China);(School of Computer Sci., Sichuan Univ., Chengdu 610064, China);(School of Computer Sci., Sichuan Univ., Chengdu 610064, China)

收稿日期:2007-06-01          年卷(期)页码:2008,40(1):107-112

期刊名称:工程科学与技术

Journal Name:Advanced Engineering Sciences

关键字:基因表达式编程;表达式树;适应度评价;

Key words:Gene Expression Programming(GEP); expression tree; fitness evaluate

基金项目:国家自然科学基金资助项目(60473071);国家科技支撑计划资助项目(2006038002003)

中文摘要

基因表达式编程(Gene Expression Programming,GEP)在处理复杂长基因时的空间、时间效率较低,为解决这一问题,提出并实现了具有线性复杂度的染色体适应度评价算法。分析了传统GEP算法中借助ET(Expression Tree)树进行染色体适应度评价的局限性;提出并实现了具有线性复杂度的染色体适应度评价算法LDecode算法;针对染色体长度、种群大小、测试数据集大小、进化代数等不同参数,对提出的染色体适应度评价算法进行了评价和分析。试验表明,提出的评价算法运行速度较传统基于ET树的G

英文摘要

The efficiency of gene expression programming (GEP) is low in processing complex gene with large length. In order to solve the problem, a novel algorithm with linear complexity was proposed. The main contributions include: 1) Analyzing the limit in conventional gene expression programming, 2) Proposing a novel LDecode algorithm to evaluate the fitness of chromosome speedy.The extensive experiments demonstrated that this algorithm is faster than traditional one by 4.5~5.1 times on different parameters, and the time complexity and space complexity are linear.

关闭

Copyright © 2020四川大学期刊社 版权所有.

地址:成都市一环路南一段24号

邮编:610065