The second edition of this bestseller provides a practical and accessible introduction to the
main concepts, foundation, and applications of Bayesian networks. This edition contains a …

Bayesian networks are quantitative modeling tools whose applications to the maritime traffic
safety context are becoming more popular. This paper discusses the utilization of Bayesian …

The influences of the variables in a Bayesian belief network model for estimating the role of
human factors on ship collision probability in the Gulf of Finland are studied for discovering …

Learning management systems (LMSs) such as WebCT, Blackboard, and Moodle are
commonly and successfully used in e-education. While they focus on supporting teachers in …

Most documented Bayesian network (BN) applications have been built through knowledge
elicitation from domain experts (DEs). The difficulties involved have led to growing interest in …

Modelling the risk factors driving an environmental problem can be problematic when
published data describing variables and their interactions are sparse. In such cases, expert …

This document outlines an ecological risk assessment framework for the Australian irrigation
industry. The objective of the framework is to provide a robust process that will assist the …

Work in the area of risk assessment of infrastructure projects is full of different techniques;
study on the risk management factors is non-existent. It is required because such risks of …

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex
ecological problems. In a BBN, the important variables in a problem are identified and …

The environmental consequences of global climate change are predicted to have their
greatest effect at high latitudes and have great potential to impact fragile tundra ecosystems …