André de Korvin

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| In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, we have interval neural networks. By analyzing the mathematical model, we categorize general three-layer neural network training problems into two types. One of them can be(More)
In decision under uncertainty, we aim at finding a scoring procedure to determine an optimal decision without prior knowledge on the actual state of the world. It is well known that the probability approach to this problem leads to paradoxes, that are related to independence properties required on the preferences. This naturally leads us to drop additivity(More)
* This work is partially supported by an ARO grant number DAAH0495-1-0205 and an NSF grant number CDA-9522157. Abstract Current computer security systems are based on the premise that once a user presents valid credentials to the authentication system (e.g. valid ID and password), they are granted access permission to all resources assigned to the user that(More)
Targeting behavior of vehicles in the battlefield (Target Analysis) is one of the most critical tasks in Computer Generated Forces (CGF) systems. This is simply because of many complex and ambiguous factors that can effect the targeting behavior of such systems in the real world. There has been many approaches including using Fuzzy Set Theory for Target(More)