Pruning Generalized Rules for Stock Markets Accumulated by Genetic Network Programming with Rule Accumulation

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Xing:2011:PGRfSMAbGNPwRA,

• title = "Pruning Generalized Rules for Stock Markets Accumulated by Genetic Network Programming with Rule Accumulation",
• author = "Yafei Xing and Shingo Mabu and Kotaro Hirasawa",
• pages = "2473--2479",
• booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary Computation",
• year = "2011",
• editor = "Alice E. Smith",
• month = "5-8 " # jun,
• address = "New Orleans, USA",
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, genetic network programming, Finance and economics",
• DOI = "doi:10.1109/CEC.2011.5949924",
• 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.",
• 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