Update article: applicability of artificial neural networks to integrate socio-technical drivers of buildings recovery following extreme wind events.

ABSTRACT: In a companion article, previously published in Royal Society Open Science, the authors used graph theory to evaluate artificial neural network models for potential social and building variables interactions contributing to building wind damage. The results promisingly highlighted the importance of social variables in modelling damage as opposed to the traditional approach of solely considering the physical characteristics of a building. Within this update article, the same methods are used to evaluate two different artificial neural networks for modelling building repair and/or rebuild (recovery) time. By contrast to the damage models, the recovery models (RMs) consider (A) primarily social variables and then (B) introduce structural variables. These two models are then evaluated u

SUBMITTER: Pilkington SF 

PROVIDER: S-EPMC8652281 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature