Publications
2011
1.
Castejón-Limas, Manuel; Ordieres-Meré, Joaquín; González-Marcos, Ana; González-Castro, Víctor
Effort estimates through project complexity Artículo de revista
En: Annals of Operations research, vol. 186, pp. 395–406, 2011, (Publisher: Springer US).
Resumen | Enlaces | BibTeX | Etiquetas: Data Mining, ISBSG, project management
@article{castejon-limas_effort_2011,
title = {Effort estimates through project complexity},
author = {Manuel Castejón-Limas and Joaquín Ordieres-Meré and Ana González-Marcos and Víctor González-Castro},
url = {https://link.springer.com/article/10.1007/s10479-010-0776-0},
year = {2011},
date = {2011-01-01},
journal = {Annals of Operations research},
volume = {186},
pages = {395–406},
abstract = {This paper explores the role of project complexity parameters in modeling effort estimates, emphasizing the increasing attention complexity has received in project management. Traditional methods often fail in real-world applications, highlighting the need for innovative approaches. The study extends previous research by analyzing the impact of complexity using classical linear models and artificial neural networks on the International Software Benchmarking Standards Group dataset. Results demonstrate the benefits of incorporating complexity into models and show that artificial neural networks better capture the intricate nature of complex projects.},
note = {Publisher: Springer US},
keywords = {Data Mining, ISBSG, project management},
pubstate = {published},
tppubtype = {article}
}
This paper explores the role of project complexity parameters in modeling effort estimates, emphasizing the increasing attention complexity has received in project management. Traditional methods often fail in real-world applications, highlighting the need for innovative approaches. The study extends previous research by analyzing the impact of complexity using classical linear models and artificial neural networks on the International Software Benchmarking Standards Group dataset. Results demonstrate the benefits of incorporating complexity into models and show that artificial neural networks better capture the intricate nature of complex projects.