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Uncertainty Processing and Risk Monitoring in Construction Projects Using Hierarchical Probabilistic Relational Models
Author(s) -
Baudrit Cédric,
Taillandier Franck,
Tran Thi Thuy Phuong,
Breysse Denys
Publication year - 2019
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12391
Subject(s) - probabilistic logic , computer science , formalism (music) , risk analysis (engineering) , task (project management) , reliability (semiconductor) , systems engineering , artificial intelligence , engineering , medicine , art , musical , power (physics) , physics , quantum mechanics , visual arts
Construction projects do not often reach their expected results regarding time, cost, and quality, due to the internal and external environment variations. Despite a substantial literature about risk management, no generic approach is proposed to represent construction project considering together technical and human dimensions or sustainability with their uncertainties. Modeling complex dynamical systems from heterogeneous pieces of knowledge varying in precision and reliability is a challenging task. This article proposes an innovative generic and versatile approach, based on the formalism of hierarchical probabilistic relational models to analyze and to propagate uncertainty in construction project regarding different levels of knowledge. The aim is to obtain a flexible, portable, and versatile model able to simulate the behavior of complex system's entities involved in any construction project at different levels of detail while taking uncertainty into account. To illustrate and highlight this approach, an academic example and a real case are proposed.