Genetic Programming Based on an Adaptive Regularization Method
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gp-bibliography.bib Revision:1.8010
- @InProceedings{Wu:2006:iccis,
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author = "Yanling Wu and Jiangang Lu and Youxian Sun",
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title = "Genetic Programming Based on an Adaptive
Regularization Method",
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booktitle = "International Conference on Computational Intelligence
and Security, 2006",
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year = "2006",
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volume = "1",
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pages = "324--327",
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address = "Guangzhou",
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month = nov,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-4244-0605-6",
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DOI = "doi:10.1109/ICCIAS.2006.294148",
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abstract = "A proper model of a bioprocess is very important for
the development of industrial bioprocesses. Here,
genetic programming (GP) and genetic algorithm (GA) are
used to model the Avermectin fermentation process. To
get more accuracy model without losing generalisation,
a regularisation term is integrated into the fitness
function and an adaptive method to optimise
regularisation parameter is proposed to balance
training accuracy and the curvature of a nonlinear
model. Furthermore, a new protected approach is
proposed and experiments show that with the method, the
amount the undesired sharp changes in the predicting
value decreases largely",
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notes = "National Lab. of Ind. Control Technol., Zhejiang
Univ., Hangzhou",
- }
Genetic Programming entries for
Yanling Wu
Jiangang Lu
Youxian Sun
Citations