RDF/XML JSON-LD N3/Turtle RDF/JSON

Langseth, Helge Autor

Analysis of OREDA data for maintenance optimisation

  • Langseth H.
  • Haugen K.
  • Sandtorv H.

Reliability Engineering and System Safety - 1/1/1998

10.1016/s0951-8320(98)83003-2

Número de citas: 18 (Scopus)
  • CiteScore: 9,3 (2020)

Uncertainty bounds for a monotone multistate system

  • Langseth H.
  • Lindqvist B.

Probability in the Engineering and Informational Sciences - 1/12/1998

10.1017/s0269964800005179

Número de citas: 10 (Scopus)
  • CiteScore: 1,7 (2020)

Parameter learning in object-oriented Bayesian networks

  • Langseth H.
  • Bangsø O.

Annals of Mathematics and Artificial Intelligence - 1/12/2001

10.1023/a:1016769618900

Número de citas: 27 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 2,5 (2020)
  • SJR: 0,747 (2001)
  • SNIP: 1,542 (2001)
  • Categorías SJR: Applied Mathematics (Q2); Artificial Intelligence (Q2)

The SACSO methodology for troubleshooting complex systems

  • Jensen F.
  • Kjærulff U.
  • Kristiansen B.
  • Langseth H.
  • Skaanning C.
  • Vomlel J.
  • Vomlelová M.
... Ver más Contraer

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM - 1/9/2001

10.1017/s0890060401154065

Número de citas: 55 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 2,9 (2020)
  • SJR: 0,365 (2001)
  • SNIP: 0,885 (2001)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Artificial Intelligence (Q3)

Decision theoretic troubleshooting of coherent systems

  • Langseth H.
  • Jensen F.

Reliability Engineering and System Safety - 1/4/2003

10.1016/s0951-8320(02)00202-8

Número de citas: 25 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 9,3 (2020)
  • SJR: 0,414 (2003)
  • SNIP: 1,307 (2003)
  • Categorías SJR: Industrial and Manufacturing Engineering (Q1); Safety, Risk, Reliability and Quality (Q2); Applied Mathematics (Q3)
Open Access

Fusion of domain knowledge with data for structural learning in object oriented domains

  • Langseth H.
  • Nielsen T.

Journal of Machine Learning Research - 1/4/2004

10.1162/153244304773633852

Número de citas: 16 (Web of Science) 32 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,8 (2020)
  • SJR: 1,691 (2004)
  • SNIP: 6,419 (2004)
  • Categorías SJR: Artificial Intelligence (Q1); Control and Systems Engineering (Q1); Software (Q1); Statistics and Probability (Q1)

Failure modeling and maintenance optimization for a railway line

  • Hokstad P.
  • Langseth H.
  • Lindqvist B.
  • Vatn J.

International Journal of Performability Engineering - 1/1/2005

Número de citas: 8 (Scopus)
  • CiteScore: 0,8 (2020)
  • Categorías SJR: Safety, Risk, Reliability and Quality

Latent classification models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/6/2005

10.1007/s10994-005-0472-5

Número de citas: 10 (Web of Science) 13 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,1 (2020)
  • SJR: 2,604 (2005)
  • SNIP: 5,656 (2005)
  • Categorías SJR: Artificial Intelligence (Q1); Software (Q1)

Competing risks for repairable systems: A data study

  • Langseth H.
  • Lindqvist B.

Journal of Statistical Planning and Inference - 1/5/2006

10.1016/j.jspi.2004.10.032

Número de citas: 33 (Scopus)
  • Cuartil SJR: Q2
  • CiteScore: 1,4 (2020)
  • SJR: 0,937 (2006)
  • SNIP: 1,051 (2006)
  • Categorías SJR: Applied Mathematics (Q2); Statistics and Probability (Q2); Statistics, Probability and Uncertainty (Q2)

Classification using Hierarchical Naïve Bayes models

  • Langseth H.
  • Nielsen T.

Machine Learning - 1/5/2006

10.1007/s10994-006-6136-2

Número de citas: 47 (Web of Science) 62 (Scopus)
  • Cuartil SJR: Q1
  • CiteScore: 6,1 (2020)
  • SJR: 1,8 (2006)
  • SNIP: 4,144 (2006)
  • Categorías SJR: Artificial Intelligence (Q1); Software (Q1)

Applications of Bayesian networks in reliability analysis

  • Langseth H.
  • Portinale L.

Bayesian Network Technologies: Applications and Graphical Models - 1/12/2007

10.4018/978-1-59904-141-4.ch005

Número de citas: 7 (Scopus)

Bayesian networks in reliability: The good, the bad, and the ugly

  • Langseth H.

Advances in Mathematical Modeling for Reliability - 1/5/2008

Número de citas: 14 (Scopus)

Inference in hybrid Bayesian networks with Mixtures of Truncated Basis Functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Proceedings of the Sixth European Workshop on Probabilistic Graphical Models - 1/12/2012

Número de citas: 11 (Scopus)
  • Categorías SJR: Statistics and Probability

Learning hybrid bayesian networks using mixtures of truncated basis functions. Aprendizaje de redes bayesianas híbridas con mixturas de funciones base truncadas

  • Inmaculada Pérez-Bernabé
  • Antonio Salmerón Cerdán
  • Helge Langseth

2015

Número de citas:
  • Dialnet
Open Access

Parameter estimation in mixtures of truncated exponentials

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

Proceedings of the Fourth European Workshop on Probabilistic Graphical Models - 1/12/2008

Número de citas: 3 (Scopus)
  • Categorías SJR: Statistics and Probability

Local-global-learning of naive Bayesian classifier

  • Zhong S.
  • Langseth H.

2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009 - 1/12/2009

10.1109/icicic.2009.254

Número de citas: 2 (Scopus)
  • Categorías SJR: Computational Theory and Mathematics; Computer Networks and Communications; Software
Open Access

Architectures integrating case-based reasoning and Bayesian networks for clinical decision support

  • Bruland T.
  • Aamodt A.
  • Langseth H.

IFIP Advances in Information and Communication Technology - 1/1/2010

10.1007/978-3-642-16327-2-13

Número de citas: 17 (Scopus)
  • Cuartil SJR: Q4
  • CiteScore: 1 (2020)
  • SJR: 0,142 (2010)
  • SNIP: 0,273 (2010)
  • Categorías SJR: Computer Networks and Communications (Q4); Information Systems (Q4); Information Systems and Management (Q4)

Towards a more expressive model for dynamic classification

  • Zhong S.
  • Martínez A.
  • Nielsen T.
  • Langseth H.

Proceedings of the 23rd International Florida Artificial Intelligence Research Society Conference, FLAIRS-23 - 19/10/2010

Número de citas: 3 (Scopus)
  • Categorías SJR: Artificial Intelligence; Control and Systems Engineering
Open Access

Parameter learning in MTE networks using incomplete data

  • Fernández A.
  • Langseth H.
  • Nielsen T.
  • Salmerón A.

The Fifth European Workshop on Probabilistic Graphical Models, Helsinki, Finland, 12/09/2010 - 1/12/2010

Número de citas: 4 (Scopus)
  • Categorías SJR: Statistics and Probability

Extended abstract: Combining CBR and BN using metareasoning

  • Houeland T.
  • Bruland T.
  • Aamodt A.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

10.3233/978-1-60750-754-3-189

Número de citas: 1 (Scopus)
  • Cuartil SJR: Q3
  • CiteScore: 0,6 (2020)
  • SJR: 0,246 (2011)
  • SNIP: 0,583 (2011)
  • Categorías SJR: Artificial Intelligence (Q3)

Extended abstract: A design for a tourist CF system

  • Lillegraven T.
  • Wolden A.
  • Kofod-Petersen A.
  • Langseth H.

Frontiers in Artificial Intelligence and Applications - 1/1/2011

10.3233/978-1-60750-754-3-193

Número de citas:
  • Cuartil SJR: Q3
  • CiteScore: 0,6 (2020)
  • SJR: 0,246 (2011)
  • SNIP: 0,583 (2011)
  • Categorías SJR: Artificial Intelligence (Q3)

A hybrid CBR and BN architecture refined through data analysis

  • Bruland T.
  • Aamodt A.
  • Langseth H.

International Conference on Intelligent Systems Design and Applications, ISDA - 1/12/2011

10.1109/isda.2011.6121773

Número de citas: 4 (Scopus)
  • Categorías SJR: Artificial Intelligence; Computer Science Applications; Control and Systems Engineering; Signal Processing
Open Access

Mixtures of truncated basis functions

  • Langseth H.
  • Nielsen T.
  • Rumí R.
  • Salmerón A.

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING - 1/2/2012

10.1016/j.ijar.2011.10.004

Número de citas: 56 (Web of Science) 55 (Scopus)
  • Cuartil JCR: Q2 (2012)
  • Cuartil SJR: Q1
  • Factor Impacto JCR: 1,729 (2012)
  • Impacto Normalizado por Categoría: 1,763 (2012)
  • CiteScore: 7,1 (2020)
  • SJR: 1,494 (2012)
  • SNIP: 2,132 (2012)
  • Impacto JCR a 5 años: 2,165
  • Categorías JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
  • Categorías SJR: Applied Mathematics (Q1); Artificial Intelligence (Q1); Software (Q1); Theoretical Computer Science (Q1)
Open Access

Fast approximate inference in hybrid Bayesian networks using dynamic discretisation

  • Langseth H.
  • Marquez D.
  • Neil M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 23/10/2013

10.1007/978-3-642-38637-4_23

Número de citas: 2 (Scopus)
  • CiteScore: 1,8 (2020)
  • SJR: 0,36 (2013)
  • SNIP: 0,775 (2013)

Este autor no tiene patentes.

Este autor no tiene informes ni otros tipos de publicaciones.

Scopus: 18

Web of Science: 12

Scopus: 33

Web of Science: 13

Última actualización de los datos: 4/05/24 9:22
Próxima recolección programada: 11/05/24 3:00