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This paper describes the use of Artificial Neural Networks (ANNs) for the short term prediction of maximum ozone concentrations in the East Austrian region. Various Multilayer Perceptron topologies (MLPs), Elman Networks (EN) and Modified Elman Networks (MEN) were tested. The individual models used ozone, temperature, cloud cover and wind data taken from(More)
Finding and fixing faults in programs is usually an expensive and tedious task. Consequently the development of intelligent debugging tools that aid the programmer in this task is a topic of major industrial interest. This work describes two representations for applying model-based diagnosis to Java programs, a technique that permits locating (and partly(More)
With recent research showing that consistency based diagnosis can be used to model programs written in imperative programming languages for debugging purposes, it has been possible to develop debugging environments that provide interactive support to the developer, homing in on individual faults within a few interactions. In addition to complexity results,(More)
Model-based diagnosis is a successful AI technique for locating and identifying faults in technical systems. Extending previous research on model-based diagnosis support for fault search in technical designs, we are building a model-based debugger for Java programs to provide intelligent support for the programmer trying to locate the source of an error. By(More)
Model-based reasoning is a central concept in current research into intelligent diagnostic systems. It is based on the assumption that sources of incorrect behavior in technical devices can be located and identified via the existence of a model describing the basic properties of components of a certain application domain. When actual data concerning the(More)
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