Auto-Programming for Numerical Data Based on Remnant-Standard-Deviation-Guided Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{conf/icnc/ZengLMBQZ09,

• title = "Auto-Programming for Numerical Data Based on Remnant-Standard-Deviation-Guided Gene Expression Programming",
• author = "Tao Zeng and Yintian Liu and Xirong Ma and Xiaoyuan Bao and Jiangtao Qiu and Lixin Zhan",
• booktitle = "Fifth International Conference on Natural Computation, ICNC '09",
• year = "2009",
• editor = "Haiying Wang and Kay Soon Low and Kexin Wei and Junqing Sun",
• month = "14-16 " # aug,
• volume = "3",
• pages = "124--128",
• address = "Tianjian, China",
• publisher = "IEEE Computer Society",
• isbn13 = "978-0-7695-3736-8",
• keywords = "genetic algorithms, genetic programming, gene expression programming, automatic programming, mathematical model, fitness evaluation, reverse polish notation",
• bibdate = "2010-01-21",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/icnc/icnc2009-3.html#RaoWY09",
• DOI = "doi:10.1109/ICNC.2009.617",
• 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