Function finding and constants creation method in evolutionary algorithm based on overlapped gene expression

被引:0
|
作者
Peng, Jing [1 ]
Tang, Chang-jie [2 ]
Yang, Dong-qing [1 ]
机构
[1] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
[2] Sichuan Univ, Sch Comp Sci & Engn, Chengdu 610065, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金; 北京市自然科学基金;
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Evolutionary algorithm based on overlapped gene expression (EAOGE) is a new technology of evolutionary algorithm which is inspired by the overlap gene expression in biological research. Different from existing works, EAOGE suggests a new expression structure of genes, and these genes have a probability to overlapped express in some segments. It uses chromosomes of fixed length to represent expression trees of different shapes and sizes. It does unconstrained search in the genome space and still ensures validity of the expression. This paper implements EAOGE algorithm and proposes a new constants creation method. Extensive experiments show that the method significantly improves the precision in the problems of function finding, and the precision of the new method is about 12.8 times to traditional algorithm at least.
引用
收藏
页码:18 / +
页数:2
相关论文
共 50 条
  • [41] Evolutionary Tolerance-Based Gene Selection in Gene Expression Data
    Jiao, Na
    TRANSACTIONS ON ROUGH SETS XIV, 2011, 6600 : 100 - 118
  • [42] A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series
    Sara C Madeira
    Arlindo L Oliveira
    Algorithms for Molecular Biology, 4
  • [43] A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series
    Madeira, Sara C.
    Oliveira, Arlindo L.
    ALGORITHMS FOR MOLECULAR BIOLOGY, 2009, 4
  • [44] Evolutionary Algorithm based Radial Basis Function Neural Network for Function Approximation
    Kuo, R. J.
    Hu, Tung-Lai
    Chen, Zhen-Yao
    2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 324 - +
  • [45] AN EVOLUTIONARY ALGORITHM FOR ZERO-ONE NONLINEAR OPTIMIZATION PROBLEMS BASED ON AN OBJECTIVE PENALTY FUNCTION METHOD
    Meng, Zhiqing
    Dang, Chuangyin
    Jiang, Min
    Shen, Rui
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2012, 8 (5B): : 3717 - 3726
  • [46] Improved evolutionary algorithm for global optimization based on a smooth function
    No.36 Research Institute, CETC, Jiaxing 314033, China
    不详
    不详
    Jilin Daxue Xuebao (Gongxueban), 2008, 4 (865-870):
  • [47] An RNA evolutionary algorithm based on gradient descent for function optimization
    Wu, Qiuxuan
    Zhao, Zikai
    Chen, Mingming
    Chi, Xiaoni
    Zhang, Botao
    Wang, Jian
    Zhilenkov, Anton A.
    Chepinskiy, Sergey A.
    JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING, 2024, 11 (04) : 332 - 357
  • [48] Strength Pareto Evolutionary Algorithm based Gene Subset Selection
    Basu, Swagatan
    Das, Sunanda
    Ghatak, Sujata
    Das, Asit Kr
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS AND COMPUTATIONAL INTELLIGENCE (ICBDAC), 2017, : 79 - 85
  • [49] A new method for finding constant terms in the context of gene expression programming
    Liu, Yanchao
    Gao, Liang
    Dong, Yan
    Pan, Baolin
    DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 303 - 307
  • [50] The genetic algorithm based route finding method for alternative paths
    Seo, KS
    Choi, GS
    1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 2448 - 2453