Rutting Prediction Model Developed by Genetic Programming Method Through Full Scale Accelerated Pavement Testing

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@InProceedings{Chang:2008:ICNC,

• author = "Jia-Ruey Chang and Shun-Hsing Chen and Dar-Hao Chen and Yao-Bin Liu",
• title = "Rutting Prediction Model Developed by Genetic Programming Method Through Full Scale Accelerated Pavement Testing",
• booktitle = "Fourth International Conference on Natural Computation, ICNC '08",
• year = "2008",
• month = oct,
• volume = "6",
• pages = "326--330",
• 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",
• 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.",
• notes = "Discipulus Also known as \cite{4667854}",

}

Genetic Programming entries for Jia-Ruey Chang Shun-Hsing Chen Dar-Hao Chen Yao-Bin Liu

Citations