Rutting Prediction Model Developed by Genetic Programming Method Through Full Scale Accelerated Pavement Testing
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Chang:2008:ICNC,
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author = "Jia-Ruey Chang and Shun-Hsing Chen and
Dar-Hao Chen and Yao-Bin Liu",
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title = "Rutting Prediction Model Developed by Genetic
Programming Method Through Full Scale Accelerated
Pavement Testing",
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booktitle = "Fourth International Conference on Natural
Computation, ICNC '08",
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year = "2008",
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month = oct,
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volume = "6",
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pages = "326--330",
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keywords = "genetic algorithms, genetic programming, accelerated
pavement testing, load repetitions, model evaluation,
pavement performance evaluation, pavement rutting,
pavement structural number, rutting prediction model,
test pavements, wheel load, structural engineering
computing",
-
DOI = "doi:10.1109/ICNC.2008.673",
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abstract = "The application of genetic programming (GP) to
pavement performance evaluation is relatively new. This
paper both describes and demonstrates how to develop a
model to predict the pavement rutting by using GP
method. Results from closely controlled full-scale
Accelerated Pavement Testing (APT) - 7 test pavements
(264 records) from CRREL's HVS and 1 test pavement (8
records) from TxDOT's MLS - were employed to establish
a rutting prediction model. For model evaluation
purposes, additional test pavements (94 records) from
both CRREL's HVS and TxDOT's MLS were used. GP was
applied successfully to develop a rutting prediction
model that uses wheel load, load repetitions and the
pavement Structural Number (SN) as inputs. The overall
R2 for 272 records is 0.8140. The model and algorithms
proposed in this study provide a good foundation for
further refinement when additional data is available.",
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notes = "Discipulus Also known as \cite{4667854}",
- }
Genetic Programming entries for
Jia-Ruey Chang
Shun-Hsing Chen
Dar-Hao Chen
Yao-Bin Liu
Citations