Pavement maintenance and rehabilitation decisions derived by genetic programming
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gp-bibliography.bib Revision:1.7970
- @InProceedings{Chang:2010:ICNC,
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author = "Jia-Ruey Chang and Sao-Jeng Chao",
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title = "Pavement maintenance and rehabilitation decisions
derived by genetic programming",
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booktitle = "Sixth International Conference on Natural Computation
(ICNC), 2010",
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year = "2010",
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month = "10-12 " # aug,
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volume = "5",
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pages = "2439--2443",
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address = "Yantai, Shandong, China",
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abstract = "The application of genetic programming (GP) to
pavement performance evaluation is relatively new. GP
was first proposed by John R. Koza as an evolutionary
computation technique: a stochastic search method based
on the Darwinian principle of `survival of the
fittest', whereby intelligible relationships in a
system are automatically extracted and used to generate
mathematical expressions or `programs'. Nowadays, GP
has been used as an important problem-solving method
for function fitting and classification. In this paper,
an empirical study is performed to develop a pavement
maintenance and rehabilitation (M and R) decision model
by using GP. As part of the research, experienced
pavement engineers from the Taiwan Highway Bureau (THB)
conducted pavement distress surveys on seven county
roads. For each road section, the severity and coverage
of existing distresses that required M and R treatments
were separately identified and collated into an
analytical database containing 2,340 records. These
records were then used to train, validate, and apply
the M and R decision model. The finding shows that the
total accuracy of the evolved M and R decision model
was 0.903, 0.877, and 0.878 for the training,
validation, and application data set, respectively. It
proves that the GP-based M and R decision model process
makes the pavement knowledge extraction process more
systematic, easier to use and solvable with a higher
probability of success - even for complex M and R
decision problems.",
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keywords = "genetic algorithms, genetic programming, Darwinian
principle, GP-based M amp, R decision model, Taiwan
highway bureau, evolutionary computation technique,
pavement distress surveys, pavement knowledge
extraction process, pavement maintenance, pavement
performance evaluation, problem-solving method,
rehabilitation decisions, stochastic search method,
maintenance engineering, road building, search
problems, stochastic processes",
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DOI = "doi:10.1109/ICNC.2010.5583502",
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notes = "Dept. of Civil Eng. & Environ. Inf., MingHsin Univ. of
Sci. & Technol., Hsinchu, Taiwan Also known as
\cite{5583502}",
- }
Genetic Programming entries for
Jia-Ruey Chang
Sao-Jeng Chao
Citations