### Abstract

Original language | English |
---|---|

Title of host publication | Proceedings of the World Congress on Engineering 2007 |

Editors | S.I. Ao, Len Gelman, David WL Hukins, Andrew Hunter, A. M. Korsunsky |

Publisher | Newswood |

Pages | 71-76 |

Number of pages | 6 |

Volume | 1 |

ISBN (Electronic) | 9789889867157, 9789889867126 |

Publication status | Published - 30 Jun 2007 |

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### Keywords

- Particle Swarm Optimisation
- Bayesian Network Construction

### Cite this

*Proceedings of the World Congress on Engineering 2007*(Vol. 1, pp. 71-76). Newswood .

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*Proceedings of the World Congress on Engineering 2007.*vol. 1, Newswood , pp. 71-76.

**Particle swarm optimisation for learning Bayesian networks.** / Cowie, J.; Oteniya, L.; Coles, R.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Particle swarm optimisation for learning Bayesian networks

AU - Cowie, J.

AU - Oteniya, L.

AU - Coles, R.

PY - 2007/6/30

Y1 - 2007/6/30

N2 - This paper discusses the potential of Particle Swarm Optimisation (PSO) for inducing Bayesian Networks (BNs). Specifically, we detail two methods which adopt the search and score approach to BN learning. The two algorithms are similar in that they both use PSO as the search algorithm, and the K2 metric to score the resulting network. The difference lies in the way networks are constructed. The CONstruct And Repair (CONAR) algorithm generates structures, validates, and repairs if required, and the REstricted STructure (REST) algorithm, only permits valid structures to be developed. Initial experiments indicate that these approaches produce promising results when compared to other BN learning strategies.

AB - This paper discusses the potential of Particle Swarm Optimisation (PSO) for inducing Bayesian Networks (BNs). Specifically, we detail two methods which adopt the search and score approach to BN learning. The two algorithms are similar in that they both use PSO as the search algorithm, and the K2 metric to score the resulting network. The difference lies in the way networks are constructed. The CONstruct And Repair (CONAR) algorithm generates structures, validates, and repairs if required, and the REstricted STructure (REST) algorithm, only permits valid structures to be developed. Initial experiments indicate that these approaches produce promising results when compared to other BN learning strategies.

KW - Particle Swarm Optimisation

KW - Bayesian Network Construction

UR - http://www.iaeng.org/publication/WCE2007/

M3 - Conference contribution

VL - 1

SP - 71

EP - 76

BT - Proceedings of the World Congress on Engineering 2007

A2 - Ao, S.I.

A2 - Gelman, Len

A2 - Hukins, David WL

A2 - Hunter, Andrew

A2 - Korsunsky, A. M.

PB - Newswood

ER -