Auto-Programming for Numerical Data Based on Remnant-Standard-Deviation-Guided Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{conf/icnc/ZengLMBQZ09,
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title = "Auto-Programming for Numerical Data Based on
Remnant-Standard-Deviation-Guided Gene Expression
Programming",
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author = "Tao Zeng and Yintian Liu and Xirong Ma and
Xiaoyuan Bao and Jiangtao Qiu and Lixin Zhan",
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booktitle = "Fifth International Conference on Natural Computation,
ICNC '09",
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year = "2009",
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editor = "Haiying Wang and Kay Soon Low and Kexin Wei and
Junqing Sun",
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month = "14-16 " # aug,
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volume = "3",
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pages = "124--128",
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address = "Tianjian, China",
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publisher = "IEEE Computer Society",
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isbn13 = "978-0-7695-3736-8",
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keywords = "genetic algorithms, genetic programming, gene
expression programming, automatic programming,
mathematical model, fitness evaluation, reverse polish
notation",
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bibdate = "2010-01-21",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/icnc/icnc2009-3.html#RaoWY09",
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DOI = "doi:10.1109/ICNC.2009.617",
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abstract = "Automatically numerical data modeling and computer
code generation is significant for data mining, data
reverse engineering, engineering applications, etc. On
auto-programming for numerical data, a new approach,
Remnant-standard-Deviation-guided Gene Expression
Programming (RD-GEP), was proposed. New individual
structure, the K-expression to Reverse Polish Notation
code generation without expression tree construction
algorithm (K2RPN), and remnant-standard-deviation based
fitness evaluation method in RD-GEP were presented and
studied. New individual structure makes easy to I/O or
storage the candidate solution. New decoding algorithm
with linear-time complexity can simplify system
operation and unify I/O format. New evaluation
mechanism can reduce hypothesis solution space to
improve system performance and precision. Feasibility
and usability of RD-GEP were verified on various
synthetic data sets and real 'Fishcatch' data set.
Experimental results showed RD-GEP is good at
automatically modeling numerical data and generating
reverse polish notation for target model.",
- }
Genetic Programming entries for
Tao Zeng
Yintian Liu
Xirong Ma
Xiaoyuan Bao
Jiangtao Qiu
Lixin Zhan
Citations