文章基本信息

标题：A decision support system for multi-criteria assessment of large building stocks
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作者：Alessandro Carbonari ; Alessandra Corneli ; Giuseppe Martino Di Giuda 等
期刊名称：Journal of Civil Engineering and Management
印刷版ISSN：1392-3730
出版年度：2019
卷号：25
期号：5
DOI：10.3846/jcem.2019.9872
语种：English
出版社：Vilnius Gediminas Technical University
摘要：Both public administrations and private owners of large building stocks need to work out plans for the management of their property, while having to deal with yearly budget limitations. Particularly for the former, this is a rather critical challenge, since public administrations are given the responsibility of sticking to very strict budget distributions over the years. As a consequence, when planning the actions to be taken on their building stocks in order to comply with their current use and the legislation in-force, they need to classify refurbishment priorities. The aim of this paper is to develop a first tool based on Bayesian Networks that offers an effective decision support service for owners even in case some information is incomplete. This tool can be used to evaluate the compliance of existing buildings with the latest standards. The decision support platform proposed includes a multi-criteria evaluation approach combining several performance indicators, each of which related to a specific regulatory area. This tool can be applied to existing buildings, where the building with the lowest score shows the highest priority of intervention. Also, the platform performs an assessment of expected costs for required refurbishment or renovation actions.