Uriel A. García

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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)
The behavior of an equipment can be seen as the variations of some parameters when changes in the envieronment are experienced. This paper describes how Bayesian networks can be used to learn a probabilistic model of the equipment’s behavior. Using this model, it is possible to identify deviations to the normal behavior. This means that on–line diagnosis(More)
Forecasting represents a very important task for control and decision making in many fields. Forecasting the dollar price is important for global companies to plan their investments. Forecasting the wind speed for a day-ahead horizon allows dispatching clean energy efficiently. One technique developed by the artificial intelligence community that has proved(More)
The viscosity measurement and control of fuel oil in power plants is very important for a proper combustion. However, the conventional viscometers are only reliable for a short period of time. This paper proposes an on-line analytic viscosity evaluation based on energy balance applied to a piece of tube entering the fuel oil main heater and a new control(More)
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