Titlebook: Automatic Learning Techniques in Power Systems; Louis A. Wehenkel Book 1998 Springer Science+Business Media New York 1998 Counter.Soft Com

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A. C. Pic,V. A. Moore,N. A. Burnhamnetwork approaches becomes less and less relevant. This will become more obvious in the course of this and the next chapter. One of the common characteristics of these methods is that they handle input information in the form of numerical attributes. Thus all non-numerical information must be transl

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https://doi.org/10.1057/9781137388254. We start by describing probabilistic security assessment and its connection with the automatic learning framework. Then we discuss the need for enhancing automatic learning methods in order to exploit more efficiently temporal data. We conclude by proposing a software architecture which should be

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Automatic Learning Techniques in Power Systems978-1-4615-5451-6Series ISSN 2196-3185 Series E-ISSN 2196-3193