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Stock Picking
Quantitative investment methods have gained foothold in the financial world in the last ten years. This paper shows how Bayesian Networks can be used to create a computerized stock-picking model.
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Safety and Risk Evaluation - The SERENE Method
By: Hugin Expert, ESPRIT Project 22187
The SERENE (SafEty and Risk Evaluation using bayesian NEts) method is concerned with the functional safety of complex systems, particularly programmable electronic systems which fall within the scope of draft IEC 61508 and similar standards. Functional safety concerns the ability of a system to carry out the actions necessary to achieve or maintain a safe state (IEC 1995, adapted). In a complex system the demonstration of functional safety must take account of both random and systematic failures. Systematic failures include those that result from design errors. All complex systems are potentially subject to systematic failures, but this difficulty applies most of all to software, for which systematic failures are the only form of failure.
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Learning to Traverse Doors Using Bayesian Networks
By: Elena Lazkano and Basilio Sierra
Mobile robots need to navigate in their environment in order to perform useful tasks. Doors appear in almost every office-like indoor environment and often doors have to be crossed during the navigation process. We believe that visual information may help to anticipate that a door has to be crossed and that the visual information could be combined with proximity sensors in order to select a good position from which the door crossing behavior could start.
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HUGIN as a decision making tool in tunnel construction design stage
Currently European regulations on tunnel design and construction are diverse, the variation occurring even within countries and regions or departments. This together with more recent concerns regarding consequences of tunnel fires have resulted in the search of new methods to aid on the decision making at the planning stage in tunnel construction.
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Trouble Shooting - Automated Decision Support for Customer Support Operations
It is a complex task to troubleshoot a printing system that consists of several components, like the application the user is printing from, the printer driver, the network connection, the server controlling the printer, the printer itself, and all the subcomponents of these components, etc. The printer industry spends millions of dollars a year on troubleshooting operations. Given observed symptoms, this new breed of troubleshooting systems can compute optimal sequences of troubleshooting steps, and thereby reduce the expected cost of repair to a minimum.
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Data Mining - The PRONEL Method
The aim of the PRONEL project was to develop a prototype of a data mining tool that were able to extracting Bayesian network models from data in "collaboration" with an domain expert. This was achieved and a software prototype was developed. This prototype is available for download.
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