Approaches to Bayesian Network model construction

Ifeyinwa Achumba; Djamel Azzi; I. Ezebili; Sebastian Bersch

Approaches to Bayesian Network model construction

Ifeyinwa Achumba, Djamel Azzi, I. Ezebili, Sebastian Bersch

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

Bayesian Network (BN) has sound mathematical basis, enables reasoning under uncertainty, and facilitates the update of beliefs, given new evidence. It also enables the visual representation of a model. These make BN suitable for solving uncertainty problems. This chapter details BN model construction approaches and presents our experiences with selecting the optimal construction approach.

Original language	English
Title of host publication	IAENG transactions on engineering technologies: special volume of the World Congress on Engineering 2012
Editors	G. Yang, S. Ao, L. Gelman
Place of Publication	Netherlands
Publisher	Springer
Pages	461-471
Number of pages	11
Edition	229
ISBN (Print)	9789400761902
Publication status	Published - 2013

Publication series

Name	Lecture notes in electrical engineering
Publisher	Springer
Number	229

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Achumba, I., Azzi, D., Ezebili, I., & Bersch, S. (2013). Approaches to Bayesian Network model construction. In G. Yang, S. Ao, & L. Gelman (Eds.), IAENG transactions on engineering technologies: special volume of the World Congress on Engineering 2012 (229 ed., pp. 461-471). (Lecture notes in electrical engineering; No. 229). Springer. http://link.springer.com/chapter/10.1007%2F978-94-007-6190-2_35

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title = "Approaches to Bayesian Network model construction",

abstract = "Bayesian Network (BN) has sound mathematical basis, enables reasoning under uncertainty, and facilitates the update of beliefs, given new evidence. It also enables the visual representation of a model. These make BN suitable for solving uncertainty problems. This chapter details BN model construction approaches and presents our experiences with selecting the optimal construction approach.",

author = "Ifeyinwa Achumba and Djamel Azzi and I. Ezebili and Sebastian Bersch",

year = "2013",

language = "English",

isbn = "9789400761902",

series = "Lecture notes in electrical engineering",

publisher = "Springer",

number = "229",

pages = "461--471",

editor = "G. Yang and S. Ao and L. Gelman",

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Achumba, I, Azzi, D, Ezebili, I & Bersch, S 2013, Approaches to Bayesian Network model construction. in G Yang, S Ao & L Gelman (eds), IAENG transactions on engineering technologies: special volume of the World Congress on Engineering 2012. 229 edn, Lecture notes in electrical engineering, no. 229, Springer, Netherlands, pp. 461-471. <http://link.springer.com/chapter/10.1007%2F978-94-007-6190-2_35>

Approaches to Bayesian Network model construction. / Achumba, Ifeyinwa; Azzi, Djamel; Ezebili, I. et al.
IAENG transactions on engineering technologies: special volume of the World Congress on Engineering 2012. ed. / G. Yang; S. Ao; L. Gelman. 229. ed. Netherlands: Springer, 2013. p. 461-471 (Lecture notes in electrical engineering; No. 229).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

TY - CHAP

T1 - Approaches to Bayesian Network model construction

AU - Achumba, Ifeyinwa

AU - Azzi, Djamel

AU - Ezebili, I.

AU - Bersch, Sebastian

PY - 2013

Y1 - 2013

N2 - Bayesian Network (BN) has sound mathematical basis, enables reasoning under uncertainty, and facilitates the update of beliefs, given new evidence. It also enables the visual representation of a model. These make BN suitable for solving uncertainty problems. This chapter details BN model construction approaches and presents our experiences with selecting the optimal construction approach.

AB - Bayesian Network (BN) has sound mathematical basis, enables reasoning under uncertainty, and facilitates the update of beliefs, given new evidence. It also enables the visual representation of a model. These make BN suitable for solving uncertainty problems. This chapter details BN model construction approaches and presents our experiences with selecting the optimal construction approach.

M3 - Chapter (peer-reviewed)

SN - 9789400761902

T3 - Lecture notes in electrical engineering

SP - 461

EP - 471

BT - IAENG transactions on engineering technologies: special volume of the World Congress on Engineering 2012

A2 - Yang, G.

A2 - Ao, S.

A2 - Gelman, L.

PB - Springer

CY - Netherlands

ER -

Approaches to Bayesian Network model construction

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