Discovery of Mineralization Predication Classification Rules by Using Gene Expression Programming Based on PCA
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gp-bibliography.bib Revision:1.8051
- @InProceedings{Zhang:2009:ICNC,
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title = "Discovery of Mineralization Predication Classification
Rules by Using Gene Expression Programming Based on
PCA",
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author = "Dongmei Zhang and Yue Huang and Jing Zhi",
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booktitle = "Fifth International Conference on Natural Computation,
2009. ICNC '09",
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year = "2009",
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pages = "540--543",
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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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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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bibdate = "2010-01-22",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/icnc/icnc2009-4.html#ZhangHZ09",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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DOI = "doi:10.1109/ICNC.2009.367",
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abstract = "Classification is one of the fundamental tasks in
geology field. In this paper, we propose an
evolutionary approach for discovering classification
rules of mineralization predication from distinct
combinations of geochemistry elements by using gene
expression programming (GEP). The innovative part of
the paper presents integrated/hybrid model-combine GEP
evolution modeling with Principal Component Analysis
(PCA), which reduce multidimensional data sets. Mineral
deposit with tin and copper in Gejiu is chosen as the
research area. MAPGIS and MORPAS are used to extract
the value of ore-controlled factors by mapping geologic
maps into grid cell. Case study illustrates the
proposed GEP approach Based on PCA is more efficient
and accurate in a large searching space, compared with
Decision Tree (C4.5) and Bayesian Networks.",
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notes = "Also known as \cite{5367093}",
- }
Genetic Programming entries for
Dongmei Zhang
Yue Huang
Jing Zhi
Citations