Pruning Generalized Rules for Stock Markets Accumulated by Genetic Network Programming with Rule Accumulation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Xing:2011:PGRfSMAbGNPwRA,
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title = "Pruning Generalized Rules for Stock Markets
Accumulated by Genetic Network Programming with Rule
Accumulation",
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author = "Yafei Xing and Shingo Mabu and Kotaro Hirasawa",
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pages = "2473--2479",
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booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
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year = "2011",
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editor = "Alice E. Smith",
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month = "5-8 " # jun,
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address = "New Orleans, USA",
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, genetic
network programming, Finance and economics",
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DOI = "doi:10.1109/CEC.2011.5949924",
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abstract = "A new strategy on pruning rules accumulated by Genetic
Network Programming with Rule Accumulation (GNP-RA) has
been proposed in this paper. The generalised rules
extracted by training GNP are pruned by GA in the
validation phase. Each rule has two variables: U and N.
Variable U determines if the rule is used or not, while
variable N shows that the information on N days is
used. By mutating variables U and N of each rule, the
portfolio of U and N is changed, as a result, the rules
are pruned. The performance of the pruned rules is
tested in the testing phase, meanwhile, the best
mutation rates for variable U and variable N are also
studied. The simulation results show that the pruned
rules work better than the rules without pruning.",
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notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Yafei Xing
Shingo Mabu
Kotaro Hirasawa
Citations