SEDRET — an intelligent system for the diagnosis and prediction of events in power plants

@inproceedings{ArroyoFigueroaa2000SEDRETA,
  title={SEDRET — an intelligent system for the diagnosis and prediction of events in power plants},
  author={G. Arroyo-Figueroaa and Y. Alvareza and L. E. Sucarb},
  year={2000}
}
  • G. Arroyo-Figueroaa, Y. Alvareza, L. E. Sucarb
  • Published 2000
Artificial Intelligence applications in large-scale industry, such as fossil power plants, require the ability to manage uncertainty and time. In this paper, we present an intelligent system to assist an operator of a power plant. This system, called SEDRET, is based on a novel knowledge representation of uncertainty and time, called Temporal Nodes Bayesian Networks (TNBN), a type of Probabilistic Temporal Network. A set of temporal nodes and a set of edge define a TNBN, each temporal node is… CONTINUE READING

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Bayesian Networks in Fault Diagnosis

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  • 2017

Towards a Framework to Detect and Prevent Non-technical Losses in Power Distribution Based on Data-Mining Techniques and Bayesian Networks

Yasmín Hernández, Gustavo Arroyo-Figueroa, Guillermo Rodríguez, Martin Santos, Hilda Escobedo
  • 2015 Fourteenth Mexican International Conference on Artificial Intelligence (MICAI)
  • 2015
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A Temporal Bayesian Network based on uncertain time interval

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