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Academic Case Stories
Analysis of tunnel accidents by using Bayesian networks
Accidents in tunnels and other underground structures often lead to serious consequences, more serious in general than would have been the case in open air. Tunnels often have to pass through mountainous regions with a lack of redundant detour routes. Additionally to the serious direct consequences in the tunnel, large societal consequences are associated with the temporary closure of such life lines. For this reason careful consideration of risk and safety in tunnels is necessary.
Assessment of offshore wind energy converters
Megawatt class wind energy converters in the offshore environment represent a great technical challenge concerning the design, construction and operation. It is planned to build large scale wind farms with a great number of identical structures. Inspection, maintenance and repair actions contribute largely to operation costs. Therefore monitoring and maintenance planning is essential for cost efficiency in order to keep wind energy production competitive.
Facing the Challenges in Food Product Design Using HUGIN
This case shows how Bayesian network technology can be used in the field of food product design. The current food market is a global market with many competitors fighting for the same consumer. Development of new products is essential to survive, but many innovations never become succesful or even fail. It is believed that a lack of fit between new products and consumer wishes is an important cause of failure. Only products that closely match to what the consumer really wants have a good chance to survive. Therefore, when developing new products, it is essential to start with the wishes of the consumer. According to Corney (2000) Bayesian Belief Networks could be used for implementation of consumer wishes in the design of new food products. This case is about the actual application of Bayesian networks for this purpose.
Bayesian networks and influence diagrams for earthquake risk management
The recent series of natural hazards (Sumatra earthquake 2004, Hurricane Katrina 2005) not only lead to an improved awareness, but also highlighted the difficulties involved in an efficient decision making process in such situations, especially in less developed countries. Consistent and quantitative risk assessment tools for buildings and infrastructure in seismic active areas are urgently needed to ensure an efficient decision making process that facilitates the optimal allocation of available economical resources for the management of risks.
BayesNetCrime: System for Analysis of the Factors Affecting Crime
Crime is an inevitable societal problem and is a major problem of the nation. Effective crime control requires accurate prediction for decision making in crime control planning. This research analyses the factors affecting crime risk, especially, murder cases in the Bangkok Metropolitan Area, Thailand by using a Bayesian Network. The results from the analysis are expected to be used for crime control planning.
Development of stochastic typhoon model in Northwest Pacific region and its application to portfolio loss estimation
Consistent and precise portfolio loss estimation due to typhoon damages is an important issue to decision makers in the insurance markets. The loss estimation with smaller uncertainties keeps the advantages in the markets. In this project a framework is established which allows the decision makers for implementing data and information concerning to typhoon events that the decision makers possess at the decision phases into the software tools, at the same rate as the data and the information are obtained.