Uriel A. García

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Introduction Due to the cleanness and low cost of wind energy, wind farms are designed to produce as much energy as possible. Wind depends on external atmospheric conditions. For energy control centers is difficult to schedule wind power energy due to its intermittency.
Several learning algorithms have been proposed to construct probabilistic models from data using the Bayesian networks mechanism. Some of them permit the participation of human experts in order to create a knowledge representation of the domain. However, multiple different models may result for the same problem using the same data set. This paper presents(More)
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