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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, M. A. P. & M. Filomena Teodoro (2025). Modeling the Service Quality Indicators TIEPI and END Using Quantile Regression. In Springer Nature Switzerland AG 2024 (Ed.), Computational Science and ItsApplications – ICCSA 2025 Workshops. (pp. 152-163). Praga
Exportar Referência (IEEE) 
M. A. Andrade and M. F. Teodoro,  "Modeling the Service Quality Indicators TIEPI and END Using Quantile Regression", in Computational Science and ItsApplications – ICCSA 2025 Workshops, Springer Nature Switzerland AG 2024, Ed., Praga, 2025, pp. 152-163
Exportar BibTeX 
@inproceedings{andrade2025_1777881304142,
	author = "Andrade, M. A. P. and M. Filomena Teodoro",
	title = "Modeling the Service Quality Indicators TIEPI and END Using Quantile Regression",
	booktitle = "Computational Science and ItsApplications – ICCSA 2025 Workshops",
	year = "2025",
	editor = "Springer Nature Switzerland AG 2024",
	volume = "",
	number = "",
	series = "",
	doi = "10.1007/978-3-031-97596-7_10",
	pages = "152-163",
	publisher = "",
	address = "Praga",
	organization = "",
	url = "https://link.springer.com/book/10.1007/978-3-031-97596-7"
}
Exportar RIS 
TY  - CPAPER
TI  - Modeling the Service Quality Indicators TIEPI and END Using Quantile Regression
T2  - Computational Science and ItsApplications – ICCSA 2025 Workshops
AU  - Andrade, M. A. P.
AU  - M. Filomena Teodoro
PY  - 2025
SP  - 152-163
SN  - 0302-9743
DO  - 10.1007/978-3-031-97596-7_10
CY  - Praga
UR  - https://link.springer.com/book/10.1007/978-3-031-97596-7
AB  - This study investigates the continuity of electricity distribution service in mainland Portugal using quantile regression models applied to two key technical indicators: TIEPI (Time of Interruption Equivalent to Installed Power) and END (Energy Not Delivered). Based on data from E-REDES (.2014–.2022), the analysis evaluates how interruption frequency and duration, measured by SAIFI (System Interruption Average Frequency Index) and SAIDI (System Interruption Average Duration
Index), affect energy supply resilience across different service quality zones and municipalities. Results show that SAIDI has a consistently positive and increasing effect on both END and TIEPI across quantiles, especially at the uppermost, indicating higher exposure to supply loss in the
Municipality Codes with po or performance. Fixed effects highlight considerable municipal level heterogeneity, while QSR zone classifications alone do not significantly explain performance after accounting for local variation. These findings support the need for geographically target investment
and regulation, and demonstrate the value of distribution sensitive modeling in infrastructure performance assessment.
ER  -