Evidence-Based Risk Management for Civil Engineering Projects Using Bayesian Belief Networks (BBN)

2018 ◽  
Author(s):  
Agata Siemaszko ◽  
Beata Grzyl ◽  
Adam Kristowski
Keyword(s):  
Risk Management ◽  
Civil Engineering ◽  
Bayesian Belief Networks ◽  
Evidence Based ◽  
Belief Networks ◽  
Engineering Projects

Use of Bayesian Belief Networks for risk management in energy distribution

2004 ◽  
pp. 814-818
Author(s):  
Gilles Deleuze ◽  
Hélène Bertin ◽  
Anne Dutfoy ◽  
Sandrine Pierlot ◽  
Olivier Pourret
Keyword(s):  
Risk Management ◽  
Energy Distribution ◽  
Bayesian Belief Networks ◽  
Belief Networks

scholarly journals Risk Diagnosis and Management with BBN for Civil Engineering Projects during Construction and Operation

2018 ◽  
Vol 63 ◽  
pp. 00004
Author(s):  
Marian W. Kembłowski ◽  
Beata Grzyl ◽  
Agata Siemaszko ◽  
Adam Kristowski
Keyword(s):  
Civil Engineering ◽  
Expert Knowledge ◽  
Bayesian Belief Networks ◽  
Background Information ◽  
Road Tunnel ◽  
Diagnosis And Management ◽  
The Road ◽  
Vistula River ◽  
Construction Operation ◽  
Engineering Projects

The authors demonstrate how expert knowledge about the construction and operation phases combined with monitoring data can be utilized for the diagnosis and management of risks typical to large civil engineering projects. The methodology chosen for estimating the probabilities of risk elements is known as Bayesian Belief Networks (BBN). Using a BBN model one can keep on updating the risk event probabilities as the new evidence (monitoring information) becomes available. Furthermore, the updated probabilities estimated using the available data for the construction phase serve as background information for the subsequent phase. The integrated two-object model of construction-operation may be then used to optimize the decision making, thus minimizing the risks. To better show how the proposed approach works the authors use the example of the road tunnel constructed and operated under the Dead Vistula River in Gdansk.

Bayesian Belief Networks as a tool for evidence-based conservation management

2007 ◽  
Vol 15 (2) ◽  
pp. 144-160 ◽  
Author(s):  
A.C. Newton ◽  
G.B. Stewart ◽  
A. Diaz ◽  
D. Golicher ◽  
A.S. Pullin
Keyword(s):  
Conservation Management ◽  
Bayesian Belief Networks ◽  
Evidence Based ◽  
Belief Networks

A4. UNRWA, IMPACT OF THE FIRST PHASE OF THE SECURITY BARRIER ON THE QALQILYA, TULKARM, AND JENIN DISTRICTS, GAZA CITY, JULY 2003 (EXCERPTS).

2003 ◽  
Vol 33 (1) ◽  
pp. 153-160
Keyword(s):  
Civil Engineering ◽  
West Bank ◽  
The West ◽  
Full Report ◽  
The World ◽  
Aid Coordination ◽  
President Bush ◽  
Engineering Projects ◽  
The U.S

The separation wall, one of the largest civil engineering projects in Israel's history, has been criticized even by the U.S. administration, with Condoleezza Rice stating at the end of June 2003 that it ““arouses our [U.S.] deep concern”” and President Bush on 25 July calling it ““a problem”” and noting that ““it is very difficult to develop confidence between the Palestinians and Israel with a wall snaking through the West Bank.”” A number of reports have already been issued concerning the wall, including reports by B'Tselem (available at www.btselem.org), the UN Office for the Coordination of Humanitarian Affairs (available at www.palestinianaid.info), and the World Bank's Local Aid Coordination Committee (LACC; also available at www.palestinianaid.info). UNRWA's report focuses on the segment of the wall already completed and is based on field visits to the areas affected by the barriers, with a special emphasis on localities with registered refugees. Notes have been omitted due to space constraints. The full report is available online at www.un.org/unrwa.

Using Bayesian network models to incorporate uncertainty in the economic analysis of pollution abatement measures under the water framework directive

2005 ◽  
Vol 5 (6) ◽  
pp. 95-104 ◽  
Author(s):  
D.N. Barton ◽  
T. Saloranta ◽  
T.H. Bakken ◽  
A. Lyche Solheim ◽  
J. Moe ◽  
...  
Keyword(s):  
Water Quality ◽  
At Risk ◽  
Economic Valuation ◽  
Pollution Abatement ◽  
Network Models ◽  
Cost Effective ◽  
Bayesian Belief Networks ◽  
Probabilistic Interpretation ◽  
Belief Networks ◽  
Benefit Cost Analysis

The evaluation of water bodies “at risk” of not achieving the Water Framework Directive's (WFD) goal of “good status” begs the question of how big a risk is acceptable before a programme of measures should be implemented. Documentation of expert judgement and statistical uncertainty in pollution budgets and water quality modelling, combined with Monte Carlo simulation and Bayesian belief networks, make it possible to give a probabilistic interpretation of “at risk”. Combined with information on abatement costs, a cost-effective ranking of measures based on expected costs and effect can be undertaken. Combined with economic valuation of water quality, the definition of “disproportionate cost” of abatement measures compared to benefits of achieving “good status” can also be given a probabilistic interpretation. Explicit modelling of uncertainty helps visualize where research and consulting efforts are most critical for reducing uncertainty. Based on data from the Morsa catchment in South-Eastern Norway, this paper discusses the relative merits of using Bayesian belief networks when integrating biophysical modelling results in the benefit-cost analysis of derogations and cost-effectiveness ranking of abatement measures under the WFD.

scholarly journals Using Bayesian Belief Networks to assess the influence of landscape connectivity on ecosystem service trade-offs and synergies in urban landscapes in the UK

2021 ◽  
Author(s):  
James D. Karimi ◽  
Jim A. Harris ◽  
Ron Corstanje
Keyword(s):  
Functional Connectivity ◽  
Ecosystem Service ◽  
Urban Areas ◽  
Landscape Connectivity ◽  
Structural Characteristics ◽  
Bird Species ◽  
Bayesian Belief Networks ◽  
Belief Networks ◽  
Patch Area ◽  
Trade Offs

Abstract Context Landscape connectivity is assumed to influence ecosystem service (ES) trade-offs and synergies. However, empirical studies of the effect of landscape connectivity on ES trade-offs and synergies are limited, especially in urban areas where the interactions between patterns and processes are complex. Objectives The objectives of this study were to use a Bayesian Belief Network approach to (1) assess whether functional connectivity drives ES trade-offs and synergies in urban areas and (2) assess the influence of connectivity on the supply of ESs. Methods We used circuit theory to model urban bird flow of P. major and C. caeruleus at a 2 m spatial resolution in Bedford, Luton and Milton Keynes, UK, and Bayesian Belief Networks (BBNs) to assess the sensitivity of ES trade-offs and synergies model outputs to landscape and patch structural characteristics (patch area, connectivity and bird species abundance). Results We found that functional connectivity was the most influential variable in determining two of three ES trade-offs and synergies. Patch area and connectivity exerted a strong influence on ES trade-offs and synergies. Low patch area and low to moderately low connectivity were associated with high levels of ES trade-offs and synergies. Conclusions This study demonstrates that landscape connectivity is an influential determinant of ES trade-offs and synergies and supports the conviction that larger and better-connected habitat patches increase ES provision. A BBN approach is proposed as a feasible method of ES trade-off and synergy prediction in complex landscapes. Our findings can prove to be informative for urban ES management.

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