Natural Selection of Asphalt Mix Stiffness Predictive Models with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Gopalakrishnan:2010:ANNIE,
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author = "Kasthurirangan Gopalakrishnan and Halil Ceylan and
Sunghwan Kim and Siddhartha K. Khaitan",
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title = "Natural Selection of Asphalt Mix Stiffness Predictive
Models with Genetic Programming",
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booktitle = "ANNIE 2010, Intelligent Engineering Systems through
Artificial Neural Networks",
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year = "2010",
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editor = "Cihan H. Dagli",
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volume = "20",
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pages = "paper 48",
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address = "St. Louis, Mo, USA",
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month = nov # " 1-3",
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organisation = "Smart Engineering Systems Laboratory, Systems
Engineering Graduate Programs, Missouri University of
Science and Technology, 600 W. 14th St., Rolla, MO
65409 USA",
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publisher = "ASME",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "9780791859599",
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DOI = "doi:10.1115/1.859599.paper48",
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abstract = "Genetic Programming (GP) is a systematic,
domain-independent evolutionary computation technique
that stochastically evolves populations of computer
programs to perform a user-defined task. Similar to
Genetic Algorithms (GA) which evolves a population of
individuals to better ones, GP iteratively transforms a
population of computer programs into a new generation
of programs by applying biologically inspired
operations such as crossover, mutation, etc. In this
paper, a population of Hot-Mix Asphalt (HMA) dynamic
modulus stiffness prediction models is genetically
evolved to better ones by applying the principles of
genetic programming. The HMA dynamic modulus (|E*|),
one of the stiffness measures, is the primary HMA
material property input in the new Mechanistic
Empirical Pavement Design Guide (MEPDG) developed under
National Cooperative Highway Research Program (NCHRP)
1-37A (2004) for the American State Highway and
Transportation Officials (AASHTO). It is shown that the
evolved HMA model through GP is reasonably compact and
contains both linear terms and low-order non-linear
transformations of input variables for
simplification.",
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notes = "http://annie.mst.edu/conference_schedule/ConferenceSchedule.html
ASME Order Number: 859599",
- }
Genetic Programming entries for
Kasthurirangan Gopalakrishnan
Halil Ceylan
Sung Hwan Kim
Siddhartha Kumar Khaitan
Citations