Publications
2019
1.
Pérez, Hilde; Sánchez-González, Lidia; Castejón-Limas, Manuel; Quintián-Pardo, Héctor; Corchado-Rodríguez, Emilio
Springer Nature, 2019.
Resumen | Enlaces | BibTeX | Etiquetas: Bio-Inspired Models, Data Mining, Hybrid Artificial Intelligence, Learning Algorithms
@book{perez-garcia_hybrid_2019,
title = {Hybrid Artificial Intelligent Systems: 14th International Conference, HAIS 2019, León, Spain, September 4–6, 2019, Proceedings},
author = {Hilde Pérez and Lidia Sánchez-González and Manuel Castejón-Limas and Héctor Quintián-Pardo and Emilio Corchado-Rodríguez},
url = {https://books.google.es/books?hl=en&lr=&id=GoOrDwAAQBAJ&oi=fnd&pg=PR5&dq=info:px8FfeDEwGkJ:scholar.google.com&ots=INirkJHhEQ&sig=ihkJ78XJKG-e8cQeYKzwXqaaGkk&redir_esc=y#v=onepage&q&f=false},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
volume = {11734},
publisher = {Springer Nature},
abstract = {This volume presents the refereed proceedings of the 14th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2019), held in León, Spain, in September 2019. It includes 64 full papers selected from 134 submissions, covering topics like data mining, knowledge discovery, bio-inspired models, learning algorithms, visual analysis, data mining applications, and hybrid intelligent applications.},
keywords = {Bio-Inspired Models, Data Mining, Hybrid Artificial Intelligence, Learning Algorithms},
pubstate = {published},
tppubtype = {book}
}
This volume presents the refereed proceedings of the 14th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2019), held in León, Spain, in September 2019. It includes 64 full papers selected from 134 submissions, covering topics like data mining, knowledge discovery, bio-inspired models, learning algorithms, visual analysis, data mining applications, and hybrid intelligent applications.
2011
2.
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.
0000
3.
Alaiz-Rodríguez, Rocio; Japkowicz, Nathalie; Tischer, Peter
ICTAI 2008 Artículo de revista
En: 0000.
Resumen | Enlaces | BibTeX | Etiquetas: Artificial Intelligence, Data Mining, machine learning
@article{alaiz-rodriguez_ictai_nodate,
title = {ICTAI 2008},
author = {Rocio Alaiz-Rodríguez and Nathalie Japkowicz and Peter Tischer},
url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4669744},
abstract = {2008 20th IEEE International
Conference on Tools with Artificial
Intelligence},
keywords = {Artificial Intelligence, Data Mining, machine learning},
pubstate = {published},
tppubtype = {article}
}
2008 20th IEEE International
Conference on Tools with Artificial
Intelligence
Conference on Tools with Artificial
Intelligence