PUMA

academical publication management
collect, organize, and share publications

( en | de )

 

Disambiguation of "Gouriveau, Rafael"

Author of the publication

copydeleteadd this publication to your clipboard
Machine health condition prediction via online dynamic fuzzy neural networks.

, , , , and . Eng. Appl. of AI, (2014)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Rafael Sendek University of Stuttgart

Rafael Horn University of Stuttgart

Rafael Jarosch

Diego Rafael Alba University of Stuttgart

Rafael Antonio Lainez Reyes University of Stuttgart

 

Other publications of authors with the same name

PEM fuel cell prognostics under variable load: A data-driven ensemble with new incremental learning., , , and . CoDIT, page 252-257. IEEE, (2016)Machine health condition prediction via online dynamic fuzzy neural networks., , , , and . Eng. Appl. of AI, (2014)ANOVA method applied to proton exchange membrane fuel cell ageing forecasting using an echo state network., , , , and . Mathematics and Computers in Simulation, (2017)Novel failure prognostics approach with dynamic thresholds for machine degradation., , and . IECON, page 4404-4409. IEEE, (2013)Defining and applying prediction performance metrics on a recurrent NARX time series model., , and . Neurocomputing, 73 (13-15): 2506-2521 (2010)Degradations analysis and aging modeling for health assessment and prognostics of PEMFC., , , , and . Rel. Eng. & Sys. Safety, (2016)Connexionist-Systems-Based Long Term Prediction Approaches for Prognostics., and . IEEE Trans. Reliability, 61 (4): 909-920 (2012)Improving accuracy of long-term prognostics of PEMFC stack to estimate remaining useful life., , , and . ICIT, page 1047-1052. IEEE, (2015)Fuel Cells prognostics using echo state network., , , , and . IECON, page 1632-1637. IEEE, (2013)Reducing arbitrary choices in model building for prognostics: An approach by applying parsimony principle on an evolving neuro-fuzzy system., , and . Microelectronics Reliability, 51 (2): 310-320 (2011)