Advances in Artificial Intelligence - IBERAMIA 2016: 15th - download pdf or read online

Nonfiction 13

By Manuel Montes y Gómez, Hugo Jair Escalante, Alberto Segura, Juan de Dios Murillo

ISBN-10: 3319479547

ISBN-13: 9783319479545

ISBN-10: 3319479555

ISBN-13: 9783319479552

This e-book constitutes the refereed court cases of the 15 Ibero-American convention on man made Intelligence, IBERAMIA 2016, held in San José, Costa Rica, in November 2016. The 34 papers provided have been conscientiously reviewed and chosen from seventy five submissions. The papers are prepared within the following topical sections: wisdom engineering, wisdom illustration and probabilistic reasoning; agent expertise and multi-agent platforms; making plans and scheduling; average language processing; laptop studying; enormous facts, wisdom discovery and knowledge mining; computing device imaginative and prescient and trend acceptance; computational intelligence delicate computing; AI in schooling, affective computing, and human-computer interaction. 

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Additional info for Advances in Artificial Intelligence - IBERAMIA 2016: 15th Ibero-American Conference on AI, San José, Costa Rica, November 23-25, 2016, Proceedings

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For all the detection networks, identify the Markov blankets of all nodes and construct the isolation network as shown in Fig. 2 [7]. The isolation network produces a vector with the probability of fault in all variables considered in the model. One important issue in this methodology is the amount of data recollected to learn the behavior model. The SCADA data set must be enough that most of the combinations of proper behavior are included in the learning data set. There could be a wide variety of normal behaviors between the variables.

The Electrical Research Institute (IIE in Spanish) possesses an experimental field with one wind turbine with the capacity to generate 300 kW. The wind turbine is controlled through a SCADA (supervisory control and data acquisition) system. The SCADA program has the function to store historical data of all variables values every 5 min. The total number of variables stored is 76. From those 76 variables, only 34 variables can be used to represent the turbine behavior. In order to create the probabilistic behavior model, a specific context is chosen.

The case study is the diagnosis of wind turbines where a model was constructed using SCADA historical data and filtering the different contexts proposed. Experiments show that it is possible to identify incipient deviations of normal behavior and the identification of the wind turbine failure. Even with the promising results obtained in the experiments, several questions remain and require future work. Some of these are the following: – Can a difference be identified between a failure in a sensor or a failure in an equipment?

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Advances in Artificial Intelligence - IBERAMIA 2016: 15th Ibero-American Conference on AI, San José, Costa Rica, November 23-25, 2016, Proceedings by Manuel Montes y Gómez, Hugo Jair Escalante, Alberto Segura, Juan de Dios Murillo


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