Aero-Engine Dynamic Start Model Based on Parsimonious Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Wei:2006:WCICA,
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author = "Xunkai Wei and Yinghong Li",
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title = "Aero-Engine Dynamic Start Model Based on Parsimonious
Genetic Programming",
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booktitle = "The Sixth World Congress on Intelligent Control and
Automation, WCICA 2006",
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year = "2006",
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volume = "1",
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pages = "1478--1482",
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address = "Dalian",
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-4244-0332-4",
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DOI = "doi:10.1109/WCICA.2006.1712595",
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abstract = "A novel parsimonious genetic programming (PGP)
algorithm together with a novel aero-engine optimum
data-driven dynamic start process model based on PGP
was proposed. The method uses traditional GP to
generate nonlinear input-output models that are
represented in a binary tree structure. It introduces
error reduction ratio (Err) to estimate the
contribution of each branch of the tree, which refers
to basic function term that cannot be decomposed any
more according to special given rule. It applies
orthogonal least squares algorithm (OLS) to eliminate
complex redundant subtrees and then enhance convergence
speed of GP. It is expected to obtain simple, reliable
and exact linear-in-parameters nonlinear model via GP
evolution algorithm. Application to real aero-engine
start process test data validates that the proposed
method can generate more robust and interpretable
models. It is a rather promising method for complex
nonlinear systems modelling with rather little prior
system knowledge",
-
notes = "Dept. of Aircraft & Power Eng., Air Force Eng. Univ.,
Xi'an",
- }
Genetic Programming entries for
Xunkai Wei
Yinghong Li
Citations