Gene expression programming function mining based upon grid
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Gene expression programming function mining based upon grid
Issue 6, Pages: 69-74(2008)
作者机构:
1. 南京邮电大学计算机学院
2. 南京邮电大学计算机学院,江苏,南京,210003
3. 南京大学计算机软件新技术国家重点实验室
4. ,江苏,南京,210093
作者简介:
基金信息:
DOI:
CLC:TP301.6
Published:2008
稿件说明:
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DENG Song1, WANG Ru-chuan1. Gene expression programming function mining based upon grid[J]. 2008, (6): 69-74.
DOI:
DENG Song1, WANG Ru-chuan1. Gene expression programming function mining based upon grid[J]. 2008, (6): 69-74.DOI:
Gene expression programming function mining based upon grid
摘要
提出了函数挖掘成功率、弱相关和函数一致性合并的概念
在此基础上给出了基于网格的GEP函数挖掘算法(GEPFM-grid
gene expression programming function mining based upon grid)。通过比较实验表明
GEPFM-grid的函数挖掘成功率和收敛速度比传统算法有着明显的提升且耗时较少。
Abstract
The concepts of success rate of function mining
weak correlation and merger of function consistency were proposed.On the basis of these
gene expression programming function mining based on grid(GEPFM-Grid) was put forward.By extensive experiment of GEPFM-grid and other traditional algorithms
the results show that success rate of function mining and convergent speed of GEPFM-grid is obviously improved