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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Andrade, A. R. & Teixeira, P. F. (2015). Statistical modelling of railway track geometry degradation using hierarchical Bayesian models. Reliability Engineering and System Safety. 142, 169-183
Exportar Referência (IEEE) 
A. R. Andrade and P. F. Teixeira,  "Statistical modelling of railway track geometry degradation using hierarchical Bayesian models", in Reliability Engineering and System Safety, vol. 142, pp. 169-183, 2015
Exportar BibTeX 
@article{andrade2015_1775514883611,
	author = "Andrade, A. R. and Teixeira, P. F.",
	title = "Statistical modelling of railway track geometry degradation using hierarchical Bayesian models",
	journal = "Reliability Engineering and System Safety",
	year = "2015",
	volume = "142",
	number = "",
	doi = "10.1016/j.ress.2015.05.009",
	pages = "169-183",
	url = "http://www.sciencedirect.com/science/article/pii/S0951832015001507"
}
Exportar RIS 
TY  - JOUR
TI  - Statistical modelling of railway track geometry degradation using hierarchical Bayesian models
T2  - Reliability Engineering and System Safety
VL  - 142
AU  - Andrade, A. R.
AU  - Teixeira, P. F.
PY  - 2015
SP  - 169-183
SN  - 0951-8320
DO  - 10.1016/j.ress.2015.05.009
UR  - http://www.sciencedirect.com/science/article/pii/S0951832015001507
AB  - Railway maintenance planners require a predictive model that can assess the railway track geometry degradation. The present paper uses a Hierarchical Bayesian model as a tool to model the main two quality indicators related to railway track geometry degradation: the standard deviation of longitudinal level defects and the standard deviation of horizontal alignment defects. Hierarchical Bayesian Models (HBM) are flexible statistical models that allow specifying different spatially correlated components between consecutive track sections, namely for the deterioration rates and the initial qualities parameters. HBM are developed for both quality indicators, conducting an extensive comparison between candidate models and a sensitivity analysis on prior distributions. HBM is applied to provide an overall assessment of the degradation of railway track geometry, for the main Portuguese railway line Lisbon-Oporto.
ER  -