A new technique for using multivariate adaptive regression splines (MARS) in pavement roughness prediction

Proceedings of the Institution of Civil Engineers: Transport

Volumn 156, Issue 1, 2003, Pages 51-55

  Attoh Okine, Nil O ^a   Mensah, Stephen ^a   Nawaiseh, M ^b  

^a UNIVERSITY OF DELAWARE   (United States)

^b FLORIDA INTERNATIONAL UNIVERSITY   (United States)

Author keywords

Pavement design; Roads and highways; Statistical analysis

Indexed keywords

FUNCTIONS; REGRESSION ANALYSIS; SURFACE ROUGHNESS;

MULTIVARIATE ADAPTIVE REGRESSION SPLINES (MARS);

PAVEMENTS;

CONSTRUCTION; PAVEMENT; ROAD; ROAD CONSTRUCTION; ROUGHNESS; STATISTICAL ANALYSIS;

EID: 0141595041     PISSN: 0965092X     EISSN: None     Source Type: Journal    
DOI: 10.1680/tran.2003.156.1.51     Document Type: Article

References (13)

1. PATERSON W. D. O. Transferable Causal Model of Roughness Progression. TRB, National Research Council, Washington, DC, 1989, Transportation Research Record 1215, pp. 70-84.
2. LUKANEN E. A. and HAN C. Performance history and prediction modeling for Minnesota pavements. Proceedings of the 3rd International Conference on Managing Pavements, San Antonio, Texas, 1994, 1, 63-73.
3. CAREY W. N. Jr and IRICK P. E. The pavement serviceability-performance concept. HRB, National Research Council, Washington, DC, 1960, Bulletin 250, pp. 40-58.
4. ATTOH-OKINE N. O. Predicting roughness progression in flexible pavements using artificial neural networks. Proceedings of the 3rd International Conference on Managing Pavements, San Antonio, Texas, 1994, 1, 55-62.
5. PATERSON W. and ATTOH-OKINE N. O. Simplified models of paved road maintenance based on HDM-III. TRB, National Research Council, Washington, DC, 1992, Transportation Research Record 1344, 99-105.
6. PATERSON W. D. O. Road Deterioration and Maintenance Effects: Models for Planning and Management. Johns Hopkins University Press, Baltimore, MD, 1987.
7. ATTOH-OKINE N. O. Flexible pavement roughness prediction using adaptive logic networks. Journal of Smart Engineering System Design, 2000, 2, 257-271.
8. FRIEDMAN J. H. Multivariate adaptive regression splines. Annals of Statistics, 1991, 19, 1-141.
9. SEKULIC S. and KOWALSKI B. MARS: a tutorial. Journal of Chemometrics, 1992, 6, 199-216.
10. STEINBERG D. An alternative to neural nets: multivariate adaptive regression splines (MARS). PC AI, 2001, 15, No. 1, January/February, 38-41.
11. SEPHTON P. Forecasting Recessions; Can We Do Better on MARS? Federal Reserve Bank of St Louis, 2001, pp. 39-48.
12. CRAVEN P. and WAHBA G. Smoothing noisy data with spline functions: estimating the correct degree of smoothing by the method of generalised cross-section. Numerische Mathematik, 1979, 31, No. 4, 317-403.
13. LEBLANC M. and TIBSHIRANI R. Adaptive principal surfaces. Journal of the American Statistical Association, 1994, 89, No. 425, 53-64.