We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks...

The purpose of this paper is the study of relationships between negative psychological features in young competitive team players via a Bayesian network (BN). The BN let us describe in graphical terms the dependencies and conditional independencies between variables in a multivariate context,...

Dam breaks have catastrophic consequences for human lives. This paper presents a new human risk analysis model (HURAM) using Bayesian networks for estimating human risks due to dam-break floods. A Bayesian network is constructed according to a logic structure of loss-of-life mechanisms. The...

The Tangjiashan landslide dam was formed during the Ms8.0 Wenchuan earthquake in 2008 and posed high risks to 1.2 million people downstream the dam. A human risk analysis model (HURAM) reported in the companion paper is applied to evaluate the human risk in the Tangjiashan landslide dam...

Integrated water resources management is a paradigm that incorporates technical, scientific, political, legislative and organizational aspects of a water system. This study presents a methodology for undertaking an integrated analysis of water systems supplied by groundwater. This methodology is...

Conditional independence graphs are now widely applied in science and industry to display interactions between large numbers of variables. However, the computational load of structure identification grows with the number of nodes in the network and the sample size. A tailored version of the PC...

The Upper Guadiana basin, in Spain, presents important conflicts between the agricultural sector and the environment due to their competence for water resources. The high development of irrigation has led to the over-exploitation of the aquifers, which are the main source of water in the area,...

We propose Bayesian Network based methods for estimating the cycle by cycle queue length distribution of a signalized intersection. Queue length here is defined as the number of vehicles in a cycle which have experienced significant delays. The data input to the methods are sample travel times...

In this paper we show how discrete and continuous variables can be combined using parametric conditional families of distributions and how the likelihood weighting method can be used for propagating uncertainty through the network in an efficient manner. To illustrate the method we use, as an...