DECISION-MAKING SUPPORT SYSTEMS IN CONSTRUCTION PROJECTS BASED ON BAYES NETWORKS
DOI:
https://doi.org/10.31649/2311-1429-2024-1-96-102Keywords:
Construction, decision-making, probability, graph model, BIM modeling, Bayesian network, artificial intelligenceAbstract
The work presents support systems for decision-making in conditions of uncertainty or incomplete information in
construction projects. With the help of integrated databases, the minimum level of information is determined, which can be
used both for data extrapolation and for filling decision-making models. In order to estimate the probability of parameters, for
example, the cost or duration of their compilation when applying BIM modeling, a hypothesis calculation was carried out, which
is based on a probabilistic graph model of networks Bayes.
On the one hand, BIM is a necessary technique both for the construction of new buildings, and on the other hand, it
receives particular attention and interest from owners of large construction funds who want to take advantage of building
information modeling to have a coordinated system for joint use during construction, modernization and operation of buildings
and structures.
Especially in a process related to the management and maintenance of large construction stocks, it involves the processing
of uncertain information in BIM. When working with existing buildings, due to the absence and/or incomplete availability of
documentation, which entails significant investments in terms of time and additional costs.
Therefore, to represent the reliability of existing data, it is worth introducing a tool based on a graphical probabilistic
Bayesian network model that offers valid decision support under uncertainty.
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