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Belief networks, also called Bayesian networks, are a form of artificial intelligence that incorporate uncertainty through probability theory and conditional dependence. Variables are graphically represented by nodes whereas conditional dependence relationships between the variables are represented by arrows. A belief network is developed by first defining… (More)

Research was undertaken to assist practitioners in undertaking Monte Carlo simulation of project schedules. A probabilistic model was developed to translate project characteristics into schedule risk boundaries. This model has been tested in several projects and performed very well. Lessons learned during the application of Monte Carlo simulation to a large… (More)

- Brenda McCabe, Joseph Ramani
- 2005

Contractor prequalification is essential in most construction projects, and the process has been performed by many different methods in practice. Data envelopment analysis (DEA) had been recognized as a useful technique to prequalify contractors by assigning relative efficiency scores. Data envelopment analysis, however, usually requires a large amount of… (More)

- Brenda McCabe
- IJTM
- 2001

- Simaan M. AbouRizk, Jingsheng Shi, Brenda McCabe, Dany Hajjar
- Winter Simulation Conference
- 1995

Presents concepts and implementations for automated construction simulation modeling for aggregate crushing plant operations (CRUISER) and for earthmoving operations (AP2-EARTH). In the automated modeling environment, the user can specify a real-world construction system: its physical components, required resources and other system information. A simulation… (More)

- Brenda McCabe
- Winter Simulation Conference
- 1998

A method for automatically improving the performance of construction operations was developed by the integration of computer simulation and belief networks. The simulation model is used to represent the operation and to determine the effect that changes in resource configuration have on the model performance. The belief network provides diagnostic analysis… (More)

- Brenda McCabe
- Winter Simulation Conference
- 2003

Research was undertaken to assist practitioners in undertaking Monte Carlo simulation of project schedules. A probabilistic model was developed to translate project characteristics into schedule risk boundaries. This model has been tested in several projects and performed very well. Lessons learned during the application of Monte Carlo simulation to a large… (More)

- Yuting Chen, Brenda McCabe, Douglas Hyatt
- Journal of safety research
- 2017

INTRODUCTION
The construction industry has hit a plateau in terms of safety performance. Safety climate is regarded as a leading indicator of safety performance; however, relatively little safety climate research has been done in the Canadian construction industry. Safety climate may be geographically sensitive, thus it is necessary to examine how the… (More)

- Ken Huen, Sabrina Ren, Susan Tighe, Brenda McCabe
- 2006

The transportation sector is an integral part of the local, provincial and national economies. There are three important issues, including mobility, safety and economics, which must be considered when highway work zones are engineered. These competing issues are important to the key parties involved in highway construction, which include the owner, the… (More)

- Brenda McCabe, Donald Ford
- Winter Simulation Conference
- 2001

This paper reviews two commonly used risk assessment tools, namely weighted scores and expected value. The limitations of weighted scores have been outlined. One of the more difficult aspects of the expected value method is to determine the probability of an event. A probabilistic modeling environment called belief networks, has been proposed as an… (More)

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