### Abstract

In the aftermath of a natural disaster, knowledge of the connectivity of different regions of infrastructure networks is crucial to aid decision makers. For large-scale networks it can be extremely time-consuming to obtain a converged estimate by performing a large number of Monte Carlo simulations to compute the network failure probability. To reduce computational requirements, this work develops a surrogate model using an AdaBoost classifier for predicting probabilities of disconnections between node clusters in lifeline infrastructure networks. The proposed approach uses spectral clustering to partition the network, and it estimates the connectivity of these clusters using an AdaBoost classifier. Numerical experiments on a California gas distribution network demonstrate that using the surrogate model to determine cluster connectivity introduces less than five percent error and is two orders of magnitude faster than methods using an exact network model to estimate the probability of network failure through Monte Carlo simulations.

Original language | English (US) |
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Title of host publication | 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015 |

Publisher | University of British Columbia |

ISBN (Electronic) | 9780888652454 |

State | Published - Jan 1 2015 |

Externally published | Yes |

Event | 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2012 - Vancouver, Canada Duration: Jul 12 2015 → Jul 15 2015 |

### Publication series

Name | 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015 |
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### Conference

Conference | 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2012 |
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Country | Canada |

City | Vancouver |

Period | 7/12/15 → 7/15/15 |

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## Cite this

*12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015*(12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015). University of British Columbia.