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Titlebook: Advances in Artificial Intelligence - IBERAMIA 2016; 15th Ibero-American Manuel Montes y Gómez,Hugo Jair Escalante,Juan de Conference pro

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https://doi.org/10.1007/978-1-4684-5781-0ed to propose an efficient manner to diagnose industrial equipment. A case study is presented with the failure identification of a wind turbine. The diagnosis is conducted when detecting deviations to the turbine normal behavior.
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Retreat of the Social? Where to?,en logistics besides this objective a minimization of the . emisions is included. For solving the bi-objective problem, we proposed the use of NISE (Noninferior Set Estimation) algorithm combined with column generation for reduce the amount of variables in the problem.
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0302-9743 mputer vision and pattern recognition; computational intelligence soft computing; AI in education, affective computing, and human-computer interaction. .978-3-319-47954-5978-3-319-47955-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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